Transmission control method and device based on image processing technology
阅读说明：本技术 一种基于图像处理技术的传输控制方法及装置 (Transmission control method and device based on image processing technology ) 是由 梁朝军 于 2021-02-09 设计创作，主要内容包括：本发明涉及图像检测技术,揭露了一种基于图像处理技术的传输控制方法,包括：对原始采集图像进行频域转换、高通滤波以及二值化处理,得到标准采集图像；根据预设骨架提取条件从标准采集图像中提取标准骨架图像；对标准骨架图像进行图像膨胀处理,得到膨胀骨架图像,提取膨胀骨架图像中目标物体的物体截面积,根据物体截面积和基于传送装置的物体体积计量公式计算目标物体的体积；若目标物体的体积与预设的体积阈值之间的差值小于预设差值,控制传送装置传输目标物体至目标地点。此外,本发明还涉及区块链技术,所述标准骨架图像可存储于区块链的节点。本发明还提出一种基于图像处理技术的传输控制装置。本发明可以解决传输装置传输物体的传输效率较低的问题。(The invention relates to an image detection technology, and discloses a transmission control method based on an image processing technology, which comprises the following steps: carrying out frequency domain conversion, high-pass filtering and binarization processing on an original collected image to obtain a standard collected image; extracting a standard skeleton image from the standard collected image according to a preset skeleton extraction condition; performing image expansion processing on the standard skeleton image to obtain an expanded skeleton image, extracting the object sectional area of a target object in the expanded skeleton image, and calculating the volume of the target object according to the object sectional area and an object volume metering formula based on a conveying device; and if the difference value between the volume of the target object and the preset volume threshold value is smaller than the preset difference value, controlling the conveying device to convey the target object to the target place. In addition, the invention also relates to a block chain technology, and the standard skeleton image can be stored in the node of the block chain. The invention also provides a transmission control device based on the image processing technology. The invention can solve the problem of low transmission efficiency of the transmission device for transmitting objects.)
1. A transmission control method based on an image processing technique, the method comprising:
acquiring an original acquisition image, and performing frequency domain conversion and high-pass filtering processing on the original acquisition image to obtain an initial acquisition image, wherein the original acquisition image comprises a target object positioned on a conveying device;
carrying out feature enhancement processing on the initial acquisition image, and carrying out binarization processing on the image after feature enhancement to obtain a standard acquisition image;
extracting a standard skeleton image from the standard collected image according to a preset skeleton extraction condition;
performing image expansion processing on the standard skeleton image to obtain an expanded skeleton image, extracting the object sectional area of the target object in the expanded skeleton image, and calculating the volume of the target object according to the object sectional area and an object volume metering formula based on the conveying device;
calculating a difference value between the volume of the target object and a preset volume threshold value;
and if the difference is smaller than the preset difference, controlling the conveying device to convey the target object to a target place.
2. The transmission control method based on image processing technology as claimed in claim 1, wherein the performing of feature enhancement processing on the initially acquired image comprises:
and carrying out graying processing on the initial acquisition image.
3. The image processing technology-based transmission control method according to claim 1, wherein the preset skeleton extraction condition includes a first skeleton extraction condition and a second skeleton extraction condition, and the extracting a standard skeleton image from the standard captured image according to the preset skeleton extraction condition includes:
judging whether a first pixel point meeting a first skeleton extraction condition exists in the standard acquisition image or not;
if the standard acquisition image exists, deleting a first pixel point in the standard acquisition image to obtain a screened skeleton image;
judging whether a second pixel point meeting a second skeleton extraction condition exists in the screened skeleton image;
and if so, deleting the second pixel points in the screened skeleton image to obtain a standard skeleton image.
4. The transmission control method based on the image processing technology as claimed in claim 1, wherein the binarizing processing on the feature-enhanced image comprises:
judging the size between the pixel value of any pixel point in the image after the characteristic enhancement and a first preset pixel threshold value;
when the pixel value is greater than or equal to the first preset pixel threshold value, enabling the pixel value to be equal to a preset first set value;
and when the pixel value is smaller than the first preset pixel threshold value, enabling the pixel value to be equal to a second preset pixel threshold value.
5. The transmission control method based on image processing technology as claimed in claim 1, wherein the performing frequency domain conversion and high-pass filtering on the original captured image to obtain an initial captured image comprises:
carrying out space fast conversion on the original collected image to obtain a fast frequency domain image;
filtering the rapid frequency domain image by using a preset filtering function to obtain a filtered image;
and carrying out frequency domain inverse transformation on the filtered image to obtain an initial acquisition image.
6. The method of claim 1, wherein the performing image dilation on the standard skeleton image to obtain a dilated skeleton image comprises:
acquiring a preset structural element, and reflecting the structural element about an original point to obtain a reflection set;
and translating the reflection set in the standard skeleton image until the reflection set is translated and at least one non-zero common element of the standard skeleton image is intersected, wherein a set formed by corresponding origin positions is an expansion skeleton image.
7. The image processing technology-based transmission control method according to any one of claims 1 to 6, wherein the extracting of the object cross-sectional area of the target object in the dilated skeleton image includes:
extracting a pixel point of which the pixel in the expansion skeleton image is the first set value according to a preset pixel extraction function;
determining the size of an image formed by the pixel points of the first set value as the pixel area;
and calculating the object sectional area of the target object corresponding to the pixel area by using a preset relation coefficient.
8. A transmission control apparatus based on an image processing technique, characterized by comprising:
the image processing module is used for acquiring an original acquisition image, and performing frequency domain conversion and high-pass filtering processing on the original acquisition image to obtain an initial acquisition image, wherein the original acquisition image comprises a target object positioned on the conveying device;
the standard collected image generation module is used for carrying out feature enhancement processing on the initial collected image and carrying out binarization processing on the image after feature enhancement to obtain a standard collected image;
the skeleton extraction module is used for extracting a standard skeleton image from the standard collected image according to preset skeleton extraction conditions;
the volume calculation module is used for performing image expansion processing on the standard skeleton image to obtain an expanded skeleton image, extracting the object sectional area of the target object in the expanded skeleton image, and calculating the volume of the target object according to the object sectional area and an object volume measurement formula based on the conveying device;
the difference value calculating module is used for calculating the difference value between the volume of the target object and a preset volume threshold value;
and the object transmission module is used for controlling the transmission device to transmit the target object to the target place if the difference value is smaller than the preset difference value.
9. The image processing technology-based transmission control device of claim 8, wherein the skeleton extraction module is specifically configured to:
judging whether a first pixel point meeting a first skeleton extraction condition exists in the standard acquisition image or not;
if the standard acquisition image exists, deleting a first pixel point in the standard acquisition image to obtain a screened skeleton image;
judging whether a second pixel point meeting a second skeleton extraction condition exists in the screened skeleton image;
and if so, deleting the second pixel points in the screened skeleton image to obtain a standard skeleton image.
10. The image processing technology-based transmission control apparatus according to claim 8 or 9, wherein the image processing module is specifically configured to:
acquiring an original acquisition image, wherein the original acquisition image comprises a target object positioned on a conveying device;
carrying out space fast conversion on the original collected image to obtain a fast frequency domain image;
filtering the rapid frequency domain image by using a preset filtering function to obtain a filtered image;
and carrying out frequency domain inverse transformation on the filtered image to obtain an initial acquisition image.
Technical Field
The present invention relates to the field of image detection, and in particular, to a transmission control method and apparatus based on an image processing technique.
Background
With the rapid development of the technology, more and more goods are exported abroad, and the goods are generally produced, packaged and output in a flow line mode in factories. Among them, the conveying device (such as a conveyor belt) becomes an indispensable tool in the whole link, and in the mass production, in order to improve the accuracy and efficiency of the conveying, the conveying control is performed according to the volume of the same batch of goods on the conveying device.
However, in the prior art, during the transmission control, the goods transmitted on the transmission device are generally output to a platform with a special measurement volume for volume detection, and then the transmission of the goods is determined to be further controlled, which may damage the normal transmission flow of the transmission device, greatly prolong the transmission time, and reduce the transmission efficiency.
Disclosure of Invention
The invention provides a transmission control method and a transmission control device based on an image processing technology, and mainly aims to improve the transmission efficiency of a transmission device for transmitting objects.
In order to achieve the above object, the present invention provides a transmission control method based on image processing technology, comprising:
acquiring an original acquisition image, and performing frequency domain conversion and high-pass filtering processing on the original acquisition image to obtain an initial acquisition image, wherein the original acquisition image comprises a target object positioned on a conveying device;
carrying out feature enhancement processing on the initial acquisition image, and carrying out binarization processing on the image after feature enhancement to obtain a standard acquisition image;
extracting a standard skeleton image from the standard collected image according to a preset skeleton extraction condition;
performing image expansion processing on the standard skeleton image to obtain an expanded skeleton image, extracting the object sectional area of the target object in the expanded skeleton image, and calculating the volume of the target object according to the object sectional area and an object volume metering formula based on the conveying device;
calculating a difference value between the volume of the target object and a preset volume threshold value;
and if the difference is smaller than the preset difference, controlling the conveying device to convey the target object to a target place.
In order to solve the above problem, the present invention also provides a transmission control apparatus based on an image processing technique, the apparatus including:
the image processing module is used for acquiring an original acquisition image, and performing frequency domain conversion and high-pass filtering processing on the original acquisition image to obtain an initial acquisition image, wherein the original acquisition image comprises a target object positioned on the conveying device;
the standard collected image generation module is used for carrying out feature enhancement processing on the initial collected image and carrying out binarization processing on the image after feature enhancement to obtain a standard collected image;
the skeleton extraction module is used for extracting a standard skeleton image from the standard collected image according to preset skeleton extraction conditions;
the volume calculation module is used for performing image expansion processing on the standard skeleton image to obtain an expanded skeleton image, extracting the object sectional area of the target object in the expanded skeleton image, and calculating the volume of the target object according to the object sectional area and an object volume measurement formula based on the conveying device;
the difference value calculating module is used for calculating the difference value between the volume of the target object and a preset volume threshold value;
and the object transmission module is used for controlling the transmission device to transmit the target object to the target place if the difference value is smaller than the preset difference value.
In order to solve the above problem, the present invention also provides an electronic device, including:
a memory storing at least one instruction; and
and the processor executes the instructions stored in the memory to realize the transmission control method based on the image processing technology.
In order to solve the above problem, the present invention further provides a computer-readable storage medium, in which at least one instruction is stored, and the at least one instruction is executed by a processor in an electronic device to implement the transmission control method based on the image processing technology.
According to the invention, the frequency domain conversion and the high-pass filtering processing are carried out on the original acquisition image, the frequency domain conversion can convert the original acquisition image from the frequency domain to the space domain for processing, the filtering processing is convenient to carry out, the high-pass filtering processing can filter out light interference such as ambient light and low-frequency components in the image to obtain the initial acquisition image, the characteristic enhancement processing and the binarization processing are carried out on the initial acquisition image, the target in the image is better highlighted, the noise in the background is removed, and the standard acquisition image is obtained. And extracting a standard skeleton image from the standard collected image according to a preset skeleton extraction condition, and performing image expansion processing on the standard skeleton image, so that a highlight area in the standard skeleton image can be amplified, and subsequent volume calculation is facilitated. Through the series of processing on the images, the corresponding object volume can be rapidly and accurately calculated according to the identified highlight area, and then the target object is conveyed, so that the transmission efficiency of the transmission device for transmitting the object is improved. Therefore, the transmission control method and the transmission control device based on the image processing technology can improve the transmission efficiency of the transmission device for transmitting the object.
In addition, the performing feature enhancement processing on the initial acquisition image includes:
and carrying out graying processing on the initial acquisition image.
The embodiment of the invention calculates the corresponding gray values of all pixel points in the initial acquisition image by carrying out gray processing on the initial acquisition image, reflects the information of the image by the brightness value and plays a role in feature enhancement.
In addition, the preset skeleton extraction condition includes a first skeleton extraction condition and a second skeleton extraction condition, extracting a standard skeleton image from the standard captured image according to the preset skeleton extraction condition includes:
judging whether a first pixel point meeting a first skeleton extraction condition exists in the standard acquisition image or not;
if the standard acquisition image exists, deleting a first pixel point in the standard acquisition image to obtain a screened skeleton image;
judging whether a second pixel point meeting a second skeleton extraction condition exists in the screened skeleton image;
and if so, deleting the second pixel points in the screened skeleton image to obtain a standard skeleton image.
According to the embodiment of the invention, the first pixel points meeting the first framework extraction condition and the second pixel points meeting the second framework extraction condition are deleted, and the standard framework image is formed according to the remaining pixel points, so that the efficiency of subsequent image processing based on the standard framework image is improved.
In addition, the binarizing processing of the feature-enhanced image includes:
judging the size between the pixel value of any pixel point in the image after the characteristic enhancement and a first preset pixel threshold value;
when the pixel value is greater than or equal to the first preset pixel threshold value, enabling the pixel value to be equal to a preset first set value;
and when the pixel value is smaller than the first preset pixel threshold value, enabling the pixel value to be equal to a second preset pixel threshold value.
According to the embodiment of the invention, the image with enhanced characteristics is subjected to binarization processing, so that the target in the image is better highlighted and the noise in the background is removed.
In addition, the frequency domain conversion and the high-pass filtering processing are performed on the original collected image to obtain an initial collected image, and the method comprises the following steps:
carrying out space fast conversion on the original collected image to obtain a fast frequency domain image;
filtering the rapid frequency domain image by using a preset filtering function to obtain a filtered image;
and carrying out frequency domain inverse transformation on the filtered image to obtain an initial acquisition image.
According to the embodiment of the invention, the original collected image can be converted from the frequency domain to the space domain for processing through the frequency domain conversion, so that the filtering processing is convenient, and the high-pass filtering processing can filter light interference such as ambient light and the like and low-frequency components in the image.
In addition, the performing image expansion processing on the standard skeleton image to obtain an expanded skeleton image includes:
acquiring a preset structural element, and reflecting the structural element about an original point to obtain a reflection set;
and translating the reflection set in the standard skeleton image until the reflection set is translated and at least one non-zero common element of the standard skeleton image is intersected, wherein a set formed by corresponding origin positions is an expansion skeleton image.
According to the embodiment of the invention, the image expansion processing is carried out on the standard skeleton image, and the highlight area in the standard skeleton image is amplified, so that the subsequent extraction of the sectional area of the object is facilitated.
In addition, the extracting the object cross-sectional area of the target object in the expanded skeleton image includes:
extracting a pixel point of which the pixel in the expansion skeleton image is the first set value according to a preset pixel extraction function;
determining the size of an image formed by the pixel points of the first set value as the pixel area;
and calculating the object sectional area of the target object corresponding to the pixel area by using a preset relation coefficient.
According to the embodiment of the invention, the corresponding object volume can be rapidly and accurately calculated according to the identified highlight area, so that the target object is transmitted, and the transmission efficiency of the transmission device for transmitting the object is improved.
Drawings
Fig. 1 is a schematic flowchart of a transmission control method based on an image processing technology according to an embodiment of the present invention;
fig. 2 is a functional block diagram of a transmission control apparatus based on image processing technology according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of an electronic device implementing the transmission control method based on the image processing technology according to an embodiment of the present invention.
The implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention more apparent, embodiments of the present invention will be described in detail below with reference to the accompanying drawings. However, it will be appreciated by those of ordinary skill in the art that numerous technical details are set forth in order to provide a better understanding of the present application in various embodiments of the present invention. However, the technical solution claimed in the present application can be implemented without these technical details and various changes and modifications based on the following embodiments.
The embodiment of the application provides a transmission control method based on an image processing technology. The execution subject of the transmission control method based on the image processing technology includes, but is not limited to, at least one of electronic devices such as a server and a terminal, which can be configured to execute the method provided by the embodiment of the present application. In other words, the transmission control method based on the image processing technology may be performed by software or hardware installed in the terminal device or the server device, and the software may be a blockchain platform. The server includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, and the like.
Fig. 1 is a schematic flow chart of a transmission control method based on an image processing technique according to an embodiment of the present invention. In this embodiment, the transmission control method based on the image processing technology includes:
and S1, acquiring an original acquisition image, and performing frequency domain conversion and high-pass filtering processing on the original acquisition image to obtain an initial acquisition image, wherein the original acquisition image comprises a target object positioned on the conveying device.
In the embodiment of the present invention, the performing frequency domain conversion and high-pass filtering on the originally acquired image to obtain an initially acquired image includes:
carrying out space fast conversion on the original collected image to obtain a fast frequency domain image;
filtering the rapid frequency domain image by using a preset filtering function to obtain a filtered image;
and carrying out frequency domain inverse transformation on the filtered image to obtain an initial acquisition image.
Specifically, the performing spatial fast conversion on the originally acquired image to obtain a fast frequency domain image includes:
and carrying out space fast conversion on the original collected image by using a preset first conversion formula to obtain a pixel value F (u, v) of the fast frequency domain image.
The preset first transformation formula is as follows:
where F (x, y) represents the pixel values of the originally acquired image, F (u, v) represents the pixel values of the fast frequency domain image, M, N represents the width and height of the originally acquired image, and j is a fixed parameter in the fast fourier transform function.
Further, in the embodiment of the present invention, a preset filtering function is used to perform filtering processing on the fast frequency domain image, so as to obtain a filtered image.
The preset filter function is:
where H (u, v) is the pixel value of the filtered image, F (u, v) is the pixel value of the fast frequency domain image, D0And n is a fixed parameter.
Preferably, n has a value of 3, D0Has a value of 130.
Because light interference such as ambient light can exist in the rapid frequency domain image, the rapid frequency domain image is filtered through a filter function, and low-frequency components in the rapid frequency domain image can be filtered.
Specifically, the performing frequency domain inverse transform on the filtered image to obtain an initial acquired image includes:
and performing frequency domain inverse conversion on the filtered image by using a preset second conversion formula to obtain a pixel value L (a, b) of the initially acquired image.
The preset second transformation formula is as follows:
where L (a, b) is the pixel value of the initial acquired image, X, Y represents the width and height of the filtered image, and j is a fixed parameter in the fast fourier transform function.
And S2, performing feature enhancement processing on the initial acquired image, and performing binarization processing on the image after feature enhancement to obtain a standard acquired image.
In the embodiment of the invention, graying processing is usually adopted to enhance the image characteristics, and commonly used image graying methods include a component method, a maximum value method, an average value method and a weighted average method.
In the scheme, a weighted average method is adopted to perform characteristic enhancement processing on the initial acquisition image.
Specifically, the performing of the feature enhancement processing on the initial acquired image includes:
and carrying out graying processing on the initial acquisition image.
Further, the graying the initially acquired image includes:
extracting a red value, a green value and a blue value of any pixel point in the initial acquisition image;
acquiring three preset component weights, multiplying the red value, the green value and the blue value respectively by the component weights, and adding to obtain a gray value of a pixel point;
until all pixel points in the initially collected image are calculated to obtain the gray value of the pixel points, and the image with enhanced characteristics is obtained.
Wherein the sum of the three preset component weights is 1.
In detail, the initially captured image is generally formed by superimposing the numerical values of three channels, that is, a red value, a green value and a blue value, each channel records the brightness value of a different pixel, the three channels are divided into 256 levels of brightness, and the value range of the brightness is 0-255. when the value of the three channels is 0, the pixel is represented as black, when the value of the three channels is 255, the pixel is represented as white, when the value of the three channels is the same, the image is changed into gray, the brightness information of each pixel in the image can be represented by any one of the red value, the green value and the blue value, and the image graying is to combine the brightness values of the three channels in the initially captured image into one brightness value, that is, a gray value, and reflect the information of the image by the brightness value.
Further, the binarizing processing the image after the feature enhancement to obtain a standard collected image includes:
judging the size between the pixel value of any pixel point in the image after the characteristic enhancement and a first preset pixel threshold value;
when the pixel value is greater than or equal to the first preset pixel threshold value, enabling the pixel value to be equal to a preset first set value;
and when the pixel value is smaller than the first preset pixel threshold value, enabling the pixel value to be equal to a second preset pixel threshold value.
In the embodiment of the present invention, the first preset pixel threshold is 255, and the second preset pixel threshold is 0.
In the embodiment of the invention, the binarization processing can better highlight the target in the image and remove the noise in the background.
And S3, extracting a standard skeleton image from the standard collected image according to preset skeleton extraction conditions.
In an embodiment of the present invention, the preset skeleton extraction condition includes a first skeleton extraction condition and a second skeleton extraction condition, and the extracting a standard skeleton image from the standard captured image according to the preset skeleton extraction condition includes:
judging whether a first pixel point meeting a first skeleton extraction condition exists in the standard acquisition image or not;
if the standard acquisition image exists, deleting a first pixel point in the standard acquisition image to obtain a screened skeleton image;
judging whether a second pixel point meeting a second skeleton extraction condition exists in the screened skeleton image;
and if so, deleting the second pixel points in the screened skeleton image to obtain a standard skeleton image.
Further, before judging whether there is a first pixel point satisfying the first skeleton extraction condition in the standard collection image, a preset number of field pixel points need to be extracted, including:
making a central pixel point in the standard acquisition image as a first pixel point;
and taking the pixel point right above the first pixel point as a searching direction, and performing field searching on the periphery of the first pixel point according to the shape of the Chinese character 'hui', so as to obtain a field pixel point set of the first pixel point.
In the embodiment of the present invention, the preset number is eight.
In detail, the extracted domain pixel points are mainly used for constructing a first skeleton extraction condition and a second skeleton extraction condition.
Specifically, whether the first pixel point meeting the first skeleton extraction condition exists in the standard acquisition image is judged, and the method comprises the following steps:
the first skeleton extraction conditions are as follows:
wherein, P1For the first pixel point, N (P)1) Is the number of non-zero neighbors of said first pixel point, A (P)1) Is represented by P2，P3，…，P9The values of these points in the order change from 0 to 1 times.
And if so, deleting the first pixel points in the standard acquisition image to obtain a screened skeleton image.
In the embodiment of the invention, if a first pixel point meeting the first skeleton extraction condition exists in the standard acquisition image, the pixel point meeting the first skeleton extraction condition is deleted, and the pixel point not meeting the first skeleton extraction condition is reserved to obtain the screened skeleton image.
Further, the judging whether a second pixel point meeting a second skeleton extraction condition exists in the screening skeleton image includes:
the second skeleton extraction conditions are as follows:
wherein, P2The second pixel point is the same as the first pixel point.
And if so, deleting the second pixel points in the screened skeleton image to obtain a standard skeleton image.
In the embodiment of the invention, if a second pixel point meeting the second skeleton extraction condition exists in the screened skeleton image, the pixel point meeting the second skeleton extraction condition is deleted, and the pixel point not meeting the second skeleton extraction condition is reserved, so that a standard skeleton image is obtained.
S4, performing image expansion processing on the standard skeleton image to obtain an expanded skeleton image, extracting the object sectional area of the target object in the expanded skeleton image, and calculating the volume of the target object according to the object sectional area and an object volume metering formula based on the conveying device.
In the embodiment of the present invention, the image expansion processing is to perform image expansion, and enlarge a highlight region in the standard skeleton image.
Specifically, the performing image expansion processing on the standard skeleton image to obtain an expanded skeleton image includes:
acquiring a preset structural element, and reflecting the structural element about an original point to obtain a reflection set;
and translating the reflection set in the standard skeleton image until the reflection set is translated and at least one non-zero common element of the standard skeleton image is intersected, wherein a set formed by corresponding origin positions is an expansion skeleton image.
Further, the extracting the object cross-sectional area of the target object in the expanded skeleton image includes:
extracting a pixel point of which the pixel in the expansion skeleton image is the first set value according to a preset pixel extraction function;
determining the size of an image formed by the pixel points of the first set value as the pixel area;
and calculating the object sectional area of the target object corresponding to the pixel area by using a preset relation coefficient.
And the preset relation coefficient is sigma, and the relation coefficient is multiplied by the area of the pixel to obtain the sectional area of the object.
In detail, the pixel area refers to an object area on the expanded skeleton image, which is identified after a series of image processing such as feature enhancement, binarization, image expansion and the like, and the object cross-sectional area is on the target object and has a corresponding relationship with the pixel area.
Further, the calculating the volume of the target object according to the object cross-sectional area and an object volume metering formula based on the conveying device comprises:
calculating the volume of the object according to the following formula:
wherein V is the volume of the object, AsThe sectional area of an object, v the conveying speed of a conveying belt, f the sampling frequency of the collected original image and f the preset parameter.
And S5, calculating the difference value between the volume of the target object and a preset volume threshold value.
In the embodiment of the invention, a preset volume threshold value is obtained, and the difference value between the volume of the target object and the preset volume threshold value is calculated.
And S6, if the difference is smaller than the preset difference, controlling the conveying device to convey the target object to a target place.
In an embodiment of the present invention, if the difference is smaller than the preset difference, the transmitting device is controlled to transmit the target object to the target location, and if the difference is greater than or equal to the preset difference, the transmitting device is not controlled to transmit the target object to the target location.
Wherein, the target place is used for storing objects with the volume passing through the set standard.
According to the embodiment of the invention, the frequency domain conversion and the high-pass filtering processing are carried out on the original collected image, the frequency domain conversion can convert the original collected image from the frequency domain to the space domain for processing, the filtering processing is convenient, the high-pass filtering processing can filter out light interference such as ambient light and low-frequency components in the image to obtain the initial collected image, the characteristic enhancement processing and the binarization processing are carried out on the initial collected image, the target in the image is better highlighted, the noise in the background is removed, and the standard collected image is obtained. And extracting a standard skeleton image from the standard collected image according to a preset skeleton extraction condition, and performing image expansion processing on the standard skeleton image, so that a highlight area in the standard skeleton image can be amplified, and subsequent volume calculation is facilitated. Through the series of processing on the images, the corresponding object volume can be rapidly and accurately calculated according to the identified highlight area, and then the target object is conveyed, so that the transmission efficiency of the transmission device for transmitting the object is improved. Therefore, the transmission control method based on the image processing technology can solve the problem of low transmission efficiency.
Fig. 2 is a functional block diagram of a transmission control apparatus based on image processing technology according to an embodiment of the present invention.
The transmission control apparatus 100 based on the image processing technology according to the present invention may be installed in an electronic device. According to the realized functions, the transmission control device 100 based on the image processing technology may include an image processing module 101, a standard acquisition image generation module 102, a skeleton extraction module 103, a volume calculation module 104, a difference calculation module 105, and an object transfer module 106. The module of the present invention, which may also be referred to as a unit, refers to a series of computer program segments that can be executed by a processor of an electronic device and that can perform a fixed function, and that are stored in a memory of the electronic device.
In the present embodiment, the functions regarding the respective modules/units are as follows:
the image processing module 101 is configured to obtain an original captured image, perform frequency domain conversion and high-pass filtering on the original captured image, and obtain an initial captured image, where the original captured image includes a target object located on a conveying device;
in the embodiment of the present invention, the image processing module 101 performs frequency domain conversion and high-pass filtering on the originally acquired image by the following method to obtain an initially acquired image:
carrying out space fast conversion on the original collected image to obtain a fast frequency domain image;
filtering the rapid frequency domain image by using a preset filtering function to obtain a filtered image;
and carrying out frequency domain inverse transformation on the filtered image to obtain an initial acquisition image.
Specifically, the performing spatial fast conversion on the originally acquired image to obtain a fast frequency domain image includes:
and carrying out space fast conversion on the original collected image by using a preset first conversion formula to obtain a pixel value F (u, v) of the fast frequency domain image.
The preset first transformation formula is as follows:
where F (x, y) represents the pixel values of the originally acquired image, F (u, v) represents the pixel values of the fast frequency domain image, M, N represents the width and height of the originally acquired image, and j is a fixed parameter in the fast fourier transform function.
Further, in the embodiment of the present invention, a preset filtering function is used to perform filtering processing on the fast frequency domain image, so as to obtain a filtered image.
The preset filter function is:
where H (u, v) is the pixel value of the filtered image, F (u, v) is the pixel value of the fast frequency domain image, D0And n is a fixed parameter.
Preferably, n has a value of 3, D0Has a value of 130.
Because light interference such as ambient light can exist in the rapid frequency domain image, the rapid frequency domain image is filtered through a filter function, and low-frequency components in the rapid frequency domain image can be filtered.
Specifically, the performing frequency domain inverse transform on the filtered image to obtain an initial acquired image includes:
and performing frequency domain inverse conversion on the filtered image by using a preset second conversion formula to obtain a pixel value L (a, b) of the initially acquired image.
The preset second transformation formula is as follows:
where L (a, b) is the pixel value of the initial acquired image, X, Y represents the width and height of the filtered image, and j is a fixed parameter in the fast fourier transform function.
The standard collected image generating module 102 is configured to perform feature enhancement processing on the initial collected image, and perform binarization processing on the feature-enhanced image to obtain a standard collected image;
in the embodiment of the present invention, the standard captured image generating module 102 generally adopts a graying process to enhance image characteristics, and commonly used image graying methods include a component method, a maximum value method, an average value method and a weighted average method.
In the scheme, a weighted average method is adopted to perform characteristic enhancement processing on the initial acquisition image.
Specifically, the performing of the feature enhancement processing on the initial acquired image includes:
and carrying out graying processing on the initial acquisition image.
Further, the graying the initially acquired image includes:
extracting a red value, a green value and a blue value of any pixel point in the initial acquisition image;
acquiring three preset component weights, multiplying the red value, the green value and the blue value respectively by the component weights, and adding to obtain a gray value of a pixel point;
until all pixel points in the initially collected image are calculated to obtain the gray value of the pixel points, and the image with enhanced characteristics is obtained.
Wherein the sum of the three preset component weights is 1.
In detail, the initially captured image is generally formed by superimposing the numerical values of three channels, that is, a red value, a green value and a blue value, each channel records the brightness value of a different pixel, the three channels are divided into 256 levels of brightness, and the value range of the brightness is 0-255. when the value of the three channels is 0, the pixel is represented as black, when the value of the three channels is 255, the pixel is represented as white, when the value of the three channels is the same, the image is changed into gray, the brightness information of each pixel in the image can be represented by any one of the red value, the green value and the blue value, and the image graying is to combine the brightness values of the three channels in the initially captured image into one brightness value, that is, a gray value, and reflect the information of the image by the brightness value.
Further, the binarizing processing the image after the feature enhancement to obtain a standard collected image includes:
judging the size between the pixel value of any pixel point in the image after the characteristic enhancement and a first preset pixel threshold value;
when the pixel value is greater than or equal to the first preset pixel threshold value, enabling the pixel value to be equal to a preset first set value;
and when the pixel value is smaller than the first preset pixel threshold value, enabling the pixel value to be equal to a second preset pixel threshold value.
In the embodiment of the present invention, the first preset pixel threshold is 255, and the second preset pixel threshold is 0.
In the embodiment of the invention, the binarization processing can better highlight the target in the image and remove the noise in the background.
The skeleton extraction module 103 is configured to extract a standard skeleton image from the standard collected image according to a preset skeleton extraction condition;
in an embodiment of the present invention, the preset skeleton extraction condition includes a first skeleton extraction condition and a second skeleton extraction condition, and the extracting a standard skeleton image from the standard captured image according to the preset skeleton extraction condition includes:
judging whether a first pixel point meeting a first skeleton extraction condition exists in the standard acquisition image or not;
if the standard acquisition image exists, deleting a first pixel point in the standard acquisition image to obtain a screened skeleton image;
judging whether a second pixel point meeting a second skeleton extraction condition exists in the screened skeleton image;
and if so, deleting the second pixel points in the screened skeleton image to obtain a standard skeleton image.
Further, before judging whether there is a first pixel point satisfying the first skeleton extraction condition in the standard collection image, a preset number of field pixel points need to be extracted, including:
making a central pixel point in the standard acquisition image as a first pixel point;
and taking the pixel point right above the first pixel point as a searching direction, and performing field searching on the periphery of the first pixel point according to the shape of the Chinese character 'hui', so as to obtain a field pixel point set of the first pixel point.
In the embodiment of the present invention, the preset number is eight.
In detail, the extracted domain pixel points are mainly used for constructing a first skeleton extraction condition and a second skeleton extraction condition.
Specifically, whether the first pixel point meeting the first skeleton extraction condition exists in the standard acquisition image is judged, and the method comprises the following steps:
the first skeleton extraction conditions are as follows:
wherein, P1For the first pixel point, N (P)1) Is the number of non-zero neighbors of said first pixel point, A (P)1) Is represented by P2，P3，…，P9The values of these points in the order change from 0 to 1 times.
And if so, deleting the first pixel points in the standard acquisition image to obtain a screened skeleton image.
In the embodiment of the invention, if a first pixel point meeting the first skeleton extraction condition exists in the standard acquisition image, the pixel point meeting the first skeleton extraction condition is deleted, and the pixel point not meeting the first skeleton extraction condition is reserved to obtain the screened skeleton image.
Further, the judging whether a second pixel point meeting a second skeleton extraction condition exists in the screening skeleton image includes:
the second skeleton extraction conditions are as follows:
wherein, P2The second pixel point is the same as the first pixel point.
And if so, deleting the second pixel points in the screened skeleton image to obtain a standard skeleton image.
In the embodiment of the invention, if a second pixel point meeting the second skeleton extraction condition exists in the screened skeleton image, the pixel point meeting the second skeleton extraction condition is deleted, and the pixel point not meeting the second skeleton extraction condition is reserved, so that a standard skeleton image is obtained.
The volume calculation module 104 is configured to perform image expansion processing on the standard skeleton image to obtain an expanded skeleton image, extract an object cross-sectional area of the target object in the expanded skeleton image, and calculate a volume of the target object according to the object cross-sectional area and an object volume measurement formula based on the conveying device;
in the embodiment of the present invention, the image expansion processing is to perform image expansion, and enlarge a highlight region in the standard skeleton image.
Specifically, the performing image expansion processing on the standard skeleton image to obtain an expanded skeleton image includes:
acquiring a preset structural element, and reflecting the structural element about an original point to obtain a reflection set;
and translating the reflection set in the standard skeleton image until the reflection set is translated and at least one non-zero common element of the standard skeleton image is intersected, wherein a set formed by corresponding origin positions is an expansion skeleton image.
Further, the extracting the object cross-sectional area of the target object in the expanded skeleton image includes:
extracting a pixel point of which the pixel in the expansion skeleton image is the first set value according to a preset pixel extraction function;
determining the size of an image formed by the pixel points of the first set value as the pixel area;
and calculating the object sectional area of the target object corresponding to the pixel area by using a preset relation coefficient.
And the preset relation coefficient is sigma, and the relation coefficient is multiplied by the area of the pixel to obtain the sectional area of the object.
In detail, the pixel area refers to an object area on the expanded skeleton image, which is identified after a series of image processing such as feature enhancement, binarization, image expansion and the like, and the object cross-sectional area is on the target object and has a corresponding relationship with the pixel area.
Further, the calculating the volume of the target object according to the object cross-sectional area and an object volume metering formula based on the conveying device comprises:
calculating the volume of the object according to the following formula:
wherein V is the volume of the object, AsThe sectional area of an object, v the conveying speed of a conveying belt, f the sampling frequency of the collected original image and f the preset parameter.
The difference calculation module 105 is configured to calculate a difference between the volume of the target object and a preset volume threshold.
In the embodiment of the invention, a preset volume threshold value is obtained, and the difference value between the volume of the target object and the preset volume threshold value is calculated.
The object transfer module 106 is configured to control the transfer device to transfer the target object to a target location if the difference is smaller than the preset difference.
In an embodiment of the present invention, if the difference is smaller than the preset difference, the transmitting device is controlled to transmit the target object to the target location, and if the difference is greater than or equal to the preset difference, the transmitting device is not controlled to transmit the target object to the target location.
Wherein, the target place is used for storing objects with the volume passing through the set standard.
According to the embodiment of the invention, the frequency domain conversion and the high-pass filtering processing are carried out on the original collected image, the frequency domain conversion can convert the original collected image from the frequency domain to the space domain for processing, the filtering processing is convenient, the high-pass filtering processing can filter out light interference such as ambient light and low-frequency components in the image to obtain the initial collected image, the characteristic enhancement processing and the binarization processing are carried out on the initial collected image, the target in the image is better highlighted, the noise in the background is removed, and the standard collected image is obtained. And extracting a standard skeleton image from the standard collected image according to a preset skeleton extraction condition, and performing image expansion processing on the standard skeleton image, so that a highlight area in the standard skeleton image can be amplified, and subsequent volume calculation is facilitated. Through the series of processing on the images, the corresponding object volume can be rapidly and accurately calculated according to the identified highlight area, and then the target object is conveyed, so that the transmission efficiency of the transmission device for transmitting the object is improved. Therefore, the transmission control device based on the image processing technology can solve the problem of low transmission efficiency.
Fig. 3 is a schematic structural diagram of an electronic device implementing a transmission control method based on an image processing technology according to an embodiment of the present invention.
The electronic device 1 may comprise a processor 10, a memory 11 and a bus, and may further comprise a computer program, such as a transmission control program 12 based on image processing technology, stored in the memory 11 and executable on the processor 10.
The memory 11 includes at least one type of readable storage medium, which includes flash memory, removable hard disk, multimedia card, card-type memory (e.g., SD or DX memory, etc.), magnetic memory, magnetic disk, optical disk, etc. The memory 11 may in some embodiments be an internal storage unit of the electronic device 1, such as a removable hard disk of the electronic device 1. The memory 11 may also be an external storage device of the electronic device 1 in other embodiments, such as a plug-in mobile hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like, which are provided on the electronic device 1. Further, the memory 11 may also include both an internal storage unit and an external storage device of the electronic device 1. The memory 11 may be used not only to store application software installed in the electronic device 1 and various types of data, such as codes of the transmission control program 12 based on the image processing technology, etc., but also to temporarily store data that has been output or is to be output.
The processor 10 may be composed of an integrated circuit in some embodiments, for example, a single packaged integrated circuit, or may be composed of a plurality of integrated circuits packaged with the same or different functions, including one or more Central Processing Units (CPUs), microprocessors, digital Processing chips, graphics processors, and combinations of various control chips. The processor 10 is a Control Unit (Control Unit) of the electronic device, connects various components of the electronic device by using various interfaces and lines, and executes various functions and processes data of the electronic device 1 by running or executing programs or modules (e.g., transmission Control programs based on image processing technology, etc.) stored in the memory 11 and calling data stored in the memory 11.
The bus may be a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. The bus is arranged to enable connection communication between the memory 11 and at least one processor 10 or the like.
Fig. 3 shows only an electronic device with components, and it will be understood by those skilled in the art that the structure shown in fig. 3 does not constitute a limitation of the electronic device 1, and may comprise fewer or more components than those shown, or some components may be combined, or a different arrangement of components.
For example, although not shown, the electronic device 1 may further include a power supply (such as a battery) for supplying power to each component, and preferably, the power supply may be logically connected to the at least one processor 10 through a power management device, so as to implement functions of charge management, discharge management, power consumption management, and the like through the power management device. The power supply may also include any component of one or more dc or ac power sources, recharging devices, power failure detection circuitry, power converters or inverters, power status indicators, and the like. The electronic device 1 may further include various sensors, a bluetooth module, a Wi-Fi module, and the like, which are not described herein again.
Further, the electronic device 1 may further include a network interface, and optionally, the network interface may include a wired interface and/or a wireless interface (such as a WI-FI interface, a bluetooth interface, etc.), which are generally used for establishing a communication connection between the electronic device 1 and other electronic devices.
Optionally, the electronic device 1 may further comprise a user interface, which may be a Display (Display), an input unit (such as a Keyboard), and optionally a standard wired interface, a wireless interface. Alternatively, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode) touch device, or the like. The display, which may also be referred to as a display screen or display unit, is suitable for displaying information processed in the electronic device 1 and for displaying a visualized user interface, among other things.
It is to be understood that the described embodiments are for purposes of illustration only and that the scope of the appended claims is not limited to such structures.
The memory 11 in the electronic device 1 stores an image processing technology based transmission control program 12 that is a combination of instructions that, when executed in the processor 10, enable:
acquiring an original acquisition image, and performing frequency domain conversion and high-pass filtering processing on the original acquisition image to obtain an initial acquisition image, wherein the original acquisition image comprises a target object positioned on a conveying device;
carrying out feature enhancement processing on the initial acquisition image, and carrying out binarization processing on the image after feature enhancement to obtain a standard acquisition image;
extracting a standard skeleton image from the standard collected image according to a preset skeleton extraction condition;
performing image expansion processing on the standard skeleton image to obtain an expanded skeleton image, extracting the object sectional area of the target object in the expanded skeleton image, and calculating the volume of the target object according to the object sectional area and an object volume metering formula based on the conveying device;
calculating a difference value between the volume of the target object and a preset volume threshold value;
and if the difference is smaller than the preset difference, controlling the conveying device to convey the target object to a target place.
Specifically, the specific implementation method of the processor 10 for the instruction may refer to the description of the relevant steps in the embodiment corresponding to fig. 1, which is not described herein again.
Further, the integrated modules/units of the electronic device 1, if implemented in the form of software functional units and sold or used as separate products, may be stored in a computer readable storage medium. The computer readable storage medium may be volatile or non-volatile. For example, the computer-readable medium may include: any entity or device capable of carrying said computer program code, recording medium, U-disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM).
The present invention also provides a computer-readable storage medium, storing a computer program which, when executed by a processor of an electronic device, may implement:
acquiring an original acquisition image, and performing frequency domain conversion and high-pass filtering processing on the original acquisition image to obtain an initial acquisition image, wherein the original acquisition image comprises a target object positioned on a conveying device;
carrying out feature enhancement processing on the initial acquisition image, and carrying out binarization processing on the image after feature enhancement to obtain a standard acquisition image;
extracting a standard skeleton image from the standard collected image according to a preset skeleton extraction condition;
performing image expansion processing on the standard skeleton image to obtain an expanded skeleton image, extracting the object sectional area of the target object in the expanded skeleton image, and calculating the volume of the target object according to the object sectional area and an object volume metering formula based on the conveying device;
calculating a difference value between the volume of the target object and a preset volume threshold value;
and if the difference is smaller than the preset difference, controlling the conveying device to convey the target object to a target place.
Finally, it should be noted that the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting, and although the present invention is described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications or equivalent substitutions may be made on the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.