阅读说明：本技术 一种商用餐厨垃圾分类处理装置 (Commercial kitchen garbage classification device ) 是由 朱海波 肖霄 于 2020-05-28 设计创作，主要内容包括：本发明提供了一种商用餐厨垃圾分类处理装置,其包括识别装置、垃圾桶、垃圾桶放置架以及移动装置；所述识别装置设置在垃圾桶放置架的上端,用于对待分类的餐厨垃圾进行识别,获得待分类的餐厨垃圾的类别,并向用户展示所述待分类的餐厨垃圾的类别；所述垃圾桶设置在所述垃圾桶放置架的内部；所述移动装置设置在所述垃圾桶放置架的下端,用于对垃圾桶放置架进行移动。本发明通过识别装置对待分类的餐厨垃圾进行识别,并向用户展示识别出的餐厨垃圾的类别,可以有效地避免用户由于忘记待分类垃圾的类别而错误地分类餐厨垃圾。(The invention provides a commercial kitchen waste classification treatment device which comprises an identification device, a garbage can placing frame and a moving device, wherein the identification device is arranged on the garbage can placing frame; the identification device is arranged at the upper end of the garbage can placing frame and is used for identifying the kitchen waste to be classified, obtaining the category of the kitchen waste to be classified and displaying the category of the kitchen waste to be classified to a user; the garbage can is arranged inside the garbage can placing frame; the moving device is arranged at the lower end of the garbage can placing frame and used for moving the garbage can placing frame. According to the invention, the kitchen waste to be classified is identified through the identification device, and the identified type of the kitchen waste is displayed for the user, so that the problem that the user wrongly classifies the kitchen waste due to forgetting the type of the waste to be classified can be effectively avoided.)

1. A commercial kitchen waste classification treatment device is characterized by comprising an identification device, a garbage can placing frame and a moving device;

the identification device is arranged at the upper end of the garbage can placing frame and is used for identifying the kitchen waste to be classified, obtaining the category of the kitchen waste to be classified and displaying the category of the kitchen waste to be classified to a user;

the garbage can is arranged inside the garbage can placing frame;

the moving device is arranged at the lower end of the garbage can placing frame and used for moving the garbage can placing frame.

2. The device for classifying and processing the commercial kitchen waste according to claim 1, further comprising a control device for controlling the identification device to be turned on and off, wherein the control device controls the identification device to be turned on and off by judging an average distance aved between a user and the garbage can within a preset time period, when the identification device is in a turned-off state, if the average distance aved is smaller than a preset average distance threshold, the control device controls the identification device to be turned on, and when the identification device is in a turned-on state, if the average distance aved is larger than the preset average distance threshold, the control device controls the identification device to be turned off;

the control device acquires the distance between NP times of users and the garbage can at fixed intervals within a preset time span, and the average distance aved is calculated in the following mode:

in the formula, np_iRepresenting the distance between the user and the trash can for the ith acquisition.

3. The commercial kitchen waste classification device according to claim 1, further comprising a compression device for compressing the kitchen waste in the garbage can, wherein the compression device is arranged inside the garbage can placing frame.

4. The commercial kitchen waste classification device according to claim 1, further comprising a power supply device, wherein the power supply device is connected with the recognition device and supplies power to the recognition device.

5. The commercial kitchen waste classification processing device according to claim 1, wherein said recognition device comprises an image acquisition module, a recognition module and a display module;

the image acquisition module is used for acquiring an image of the kitchen waste to be classified and transmitting the image to the identification module;

the identification module is used for identifying the image to obtain the category of the kitchen waste to be classified contained in the image;

the display module is used for displaying the category of the kitchen waste to be classified.

6. The commercial kitchen waste classification device according to claim 1, wherein the moving device comprises a universal wheel and a universal wheel locking device, and the universal wheel locking device is used for controlling the universal wheel to stop moving.

7. The commercial kitchen waste classification device according to claim 5, characterized in that the recognition device further comprises a voice acquisition module, the voice acquisition module is used for acquiring voice information of a user about names of the kitchen waste to be classified and transmitting the voice information to the recognition module, the recognition module recognizes the voice information, recognizes names of the kitchen waste to be classified contained in the voice information, acquires categories of the kitchen waste to be classified according to the names, and transmits the categories to the display module for displaying.

8. The device for classifying and processing the commercial kitchen waste according to claim 5, wherein the image acquisition module comprises a camera and a light supplement lamp, the camera is used for acquiring images of the kitchen waste to be classified, and the light supplement lamp is used for providing light for the camera when the light is insufficient.

9. The commercial kitchen waste classification processing device according to claim 7, wherein said voice acquisition module is a microphone.

Technical Field

The invention relates to the field of garbage classification, in particular to a commercial kitchen garbage classification treatment device.

Background

The kitchen waste is waste generated in activities such as daily life, food processing, food service, unit catering and the like of residents, and comprises abandoned vegetable leaves, leftovers, fruit peels, eggshells, tea leaves, bones and the like. The kitchen waste classified collection can reduce the waste treatment amount and treatment equipment, reduce the treatment cost, reduce the consumption of land resources and has social, economic and ecological benefits. However, due to the fact that the types of the kitchen waste are too many, people can hardly remember all the types of the kitchen waste completely, and therefore misclassification of the kitchen waste is often caused.

Disclosure of Invention

Aiming at the problems, the invention provides a commercial kitchen waste classification treatment device which comprises an identification device, a garbage can placing frame and a moving device, wherein the identification device is arranged on the garbage can;

the identification device is arranged at the upper end of the garbage can placing frame and is used for identifying the kitchen waste to be classified, obtaining the category of the kitchen waste to be classified and displaying the category of the kitchen waste to be classified to a user;

the garbage can is arranged inside the garbage can placing frame;

the moving device is arranged at the lower end of the garbage can placing frame and used for moving the garbage can placing frame.

Preferably, the commercial kitchen waste classification processing device further comprises a control device for controlling the identification device to be opened and closed, the control device controls the identification device to be opened and closed by judging the average distance aved between a user and the garbage can within a preset time length, when the identification device is in a closed state, if the average distance aved is smaller than a preset average distance threshold, the control device controls the identification device to be opened, and when the identification device is in an opened state, if the average distance aved is larger than the preset average distance threshold, the control device controls the identification device to be closed;

the control device acquires the distance between NP times of users and the garbage can at fixed intervals within a preset time span, and the average distance aved is calculated in the following mode:

in the formula, np_iRepresenting the distance between the user and the trash can for the ith acquisition.

Preferably, commercial kitchen garbage classification device still includes compressor arrangement, compressor arrangement is used for compressing the kitchen garbage in the garbage bin, compressor arrangement sets up the inside at the garbage bin rack.

Preferably, commercial kitchen garbage classification processing apparatus still includes power supply unit, power supply unit with identification device connects, for identification device supplies power.

The invention has the beneficial effects that:

according to the invention, the kitchen waste to be classified is identified through the identification device, and the identified type of the kitchen waste is displayed for the user, so that the problem that the user wrongly classifies the kitchen waste due to forgetting the type of the waste to be classified can be effectively avoided. The distance between the user and the garbage can is identified by the control device, so that whether the user uses the commercial kitchen waste classification device or not is judged, and the identification device is closed when no user uses the kitchen waste classification device, so that the energy-saving effect is achieved. The compression device is arranged, so that the garbage loading capacity of the garbage can be effectively improved.

Drawings

The invention is further illustrated by means of the attached drawings, but the embodiments in the drawings do not constitute any limitation to the invention, and for a person skilled in the art, other drawings can be obtained on the basis of the following drawings without inventive effort.

Fig. 1 is a diagram illustrating an exemplary embodiment of a commercial kitchen waste classification processing device according to the present invention.

Detailed Description

The invention is further described with reference to the following examples.

Referring to fig. 1, the commercial kitchen waste classification device of the invention comprises an identification device 1, a garbage can 2, a garbage can placing rack 3 and a moving device 4;

the identification device 1 is arranged at the upper end of the garbage can placing frame 3 and is used for identifying the kitchen waste to be classified, obtaining the category of the kitchen waste to be classified and displaying the category of the kitchen waste to be classified to a user;

the garbage can 2 is arranged inside the garbage can placing frame 3;

the moving device 4 is arranged at the lower end of the garbage can placing frame 3 and used for moving the garbage can placing frame 3.

According to the embodiment of the invention, the kitchen waste to be classified is identified through the identification device 1, and the identified type of the kitchen waste is displayed for the user, so that the problem that the user wrongly classifies the kitchen waste due to forgetting the type of the waste to be classified can be effectively avoided.

In one embodiment, the commercial kitchen waste classification processing device further comprises a control device for controlling the identification device 1 to be opened and closed, the control device controls the identification device 1 to be opened and closed by judging an average distance aved between a user and the garbage can 2 within a preset time length, when the identification device 1 is in a closed state, if the average distance aved is smaller than a preset average distance threshold value, the control device controls the identification device 1 to be opened, and when the identification device 1 is in an opened state, if the average distance aved is larger than the preset average distance threshold value, the control device controls the identification device 1 to be closed;

the control device acquires the distance between the NP times of users and the garbage can 2 at fixed intervals within a preset time span, and the average distance aved is calculated in the following mode:

in the formula, np_iRepresenting the distance between the user and the trash can 2 for the ith acquisition.

According to the embodiment of the invention, the control device is arranged to identify the average distance between the user and the garbage can 2 within the preset time length, so that whether the user uses the commercial kitchen waste classification treatment device or not is judged, and the identification device 1 is closed when no user uses the kitchen waste classification treatment device, so that the energy saving effect is achieved. Meanwhile, by means of identification of the average distance, false identification can be avoided, and sometimes the user only passes through the commercial kitchen waste classification processing device and does not intend to use the device, if the distance between the user and the garbage can 2 is measured by a single time, the false judgment rate is too high, and frequent false starting of the identification device 1 is not beneficial to energy conservation.

In one embodiment, the control device comprises a single chip microcomputer and an infrared distance sensor, the single chip microcomputer is electrically connected with the identification device 1, the single chip microcomputer obtains the distance between the NP users and the garbage can 2 at fixed intervals in a preset time length through the infrared distance sensor, and calculates the average distance aved between the users and the garbage can 2 in the preset time length.

In an embodiment, commercial kitchen garbage classification device still includes compressor arrangement, compressor arrangement is used for compressing the kitchen garbage in the garbage bin 2, compressor arrangement sets up the inside at garbage bin rack 3.

According to the embodiment of the invention, the compression device is arranged, so that the garbage loading capacity of the garbage can 2 can be effectively improved. Because the rubbish kitchen garbage piles up each other easily inside garbage bin 2 thereby leaves a large amount of spaces, reduces garbage bin 2's the ability of loading rubbish.

In one embodiment, the commercial kitchen waste classification device further comprises a power supply device, wherein the power supply device is connected with the identification device 1 and supplies power to the identification device 1.

In one embodiment, the recognition apparatus 1 includes an image acquisition module, a recognition module, and a display module;

the image acquisition module is used for acquiring an image of the kitchen waste to be classified and transmitting the image to the identification module;

the identification module is used for identifying the image to obtain the category of the kitchen waste to be classified contained in the image;

the display module is used for displaying the category of the kitchen waste to be classified.

According to the embodiment of the invention, the classification of the garbage to be classified is obtained through an image recognition mode, so that the problem of how to classify the kitchen garbage when a user does not know the name of the garbage to be classified is effectively solved. Thereby avoiding the misclassification of the kitchen waste.

In one embodiment, the display module comprises an OLED display screen.

In one embodiment, the identification module comprises a graying module, a brightness adjusting module, a noise reduction module, a feature extraction module and a feature matching module;

the graying module is used for performing graying processing on the image of the kitchen waste to be classified to obtain a grayscale image;

the brightness adjusting module is used for adjusting the brightness of the gray level image to obtain a brightness adjusting image;

the noise reduction module is used for carrying out noise reduction processing on the brightness adjustment image to obtain a noise reduction image;

the characteristic extraction module is used for extracting the characteristics of the noise reduction image to obtain the characteristic data of the kitchen waste;

the characteristic matching module is used for matching the characteristic data of the kitchen waste with pre-stored standard characteristic data of the kitchen waste type, so that the type of the kitchen waste is identified, and the type of the waste classification to which the kitchen waste to be classified belongs is determined from the pre-stored classification standard according to the type of the kitchen waste.

In one embodiment, the categories include recyclables, wet waste, dry waste, hazardous waste.

In one embodiment, the performing brightness adjustment processing on the grayscale image to obtain a brightness-adjusted image includes:

the grayscale image f (x, y) is brightness-adjusted as follows:

in the formula, af (x, y) represents a brightness adjustment image obtained after brightness adjustment, (x, y) represents coordinates of pixel points, gt represents an image segmentation threshold, tf represents a total number of gray levels of a gray image,indicating a preset brightness adjustment control coefficient.

According to the embodiment of the invention, the influence of uneven brightness distribution of the gray level image on the subsequent identification of the garbage classification type to which the kitchen garbage belongs can be effectively avoided by performing brightness adjustment processing on the gray level image.

In one embodiment, the image segmentation threshold gt is obtained by the otsu algorithm.

In one embodiment, the performing noise reduction processing on the brightness adjustment image to obtain a noise-reduced image includes:

performing pulse noise reduction processing on the brightness adjusting image to obtain a pulse-removed image;

and carrying out Gaussian noise reduction processing on the pulse-removed image to obtain a noise-reduced image.

In one embodiment, the performing the impulse noise reduction on the brightness adjustment image to obtain the de-impulse image includes:

the impulse noise factor mqx for the pixel currently being processed in the luma-adjusted image is calculated using the following formula:

in the equation, tar represents a pixel currently being processed, nb represents a set of neighborhood pixels of (2k +1) × (2k +1) size of tar, nonb represents a total number of elements in nb, ly represents elements in nb, dma represents a maximum value of g (ly) -g (tar), dmi represents a minimum value of g (ly) -g (tar), g (ly) represents a gray value of element ly in nb, g (tar) represents a gray value of tar, represents a gray value of 0 degree in direction, represents a preset constant-type impulse noise reduction adjustment parameter, v1, v2, v3, v4 represent a maximum value of neighborhood pixels in directions of 0 degree, 45 degree, 90 degree, 135 degree in a coordinate system with a position of tar as an origin, vma represents a minimum value of v1, 2, v3, v4, and vmi represents a minimum value of v1, v2, v3, v 4;

comparing mqx with a preset pulse noise point threshold value mqt, if mqx is greater than mqt, the currently processed pixel point is a pulse noise point, otherwise, the currently processed pixel point is a pulse noise point and does not belong to a pulse noise point;

for the impulse noise point mqr, the filtering process is performed using the following formula:

in the formula, g (amq)' indicates the gray value of mqr after filtering, γ 1 and γ 2 are preset weight coefficients, avem indicates the gray average value in a neighborhood LY2 with the size of (2k2+1) × (2k2+1) in mqr, z1 indicates the number of pixels with gray values larger than mqr in LY2, and z2 indicates the number of pixels with gray values smaller than or equal to mqr in LY 2.

In the embodiment of the invention, whether the pixel tar currently being processed is a pulse pixel is judged by calculating mqx, the difference of the gray value between the tar and the neighborhood of (2k +1) × (2k +1) is considered in the calculation of mqx, meanwhile, the influence of the extreme pixel value difference on mqx is eliminated, the calculation accuracy of mqx is improved, meanwhile, the variances of the neighborhood pixels in the directions of 0 degree, 45 degrees, 90 degrees and 135 degrees are also considered, the false identification of the image edge pixel can be avoided, and the edge information of the image is effectively retained.

In one embodiment, the performing gaussian noise reduction processing on the de-pulse image to obtain a noise-reduced image includes:

performing wavelet decomposition on the pulse-removed image to obtain a high-frequency coefficient image and a low-frequency coefficient image;

carrying out self-adaptive threshold value processing on the high-frequency coefficient image to obtain a high-frequency coefficient image subjected to the self-adaptive threshold value processing;

carrying out equalization processing on the low-frequency coefficient image to obtain a low-frequency coefficient image after equalization processing;

and performing wavelet reconstruction on the high-frequency coefficient image subjected to the adaptive threshold processing and the low-frequency coefficient image subjected to the equalization processing to obtain a noise reduction image.

In an embodiment, the performing adaptive threshold processing on the high-frequency coefficient image to obtain the high-frequency coefficient image after adaptive threshold processing includes:

the adaptive threshold processing is performed on the high frequency coefficient image using the following function:

in the formula, gp represents a high-frequency coefficient image obtained by wavelet decomposition, gpt represents a preset threshold value, Φ represents an expansion adjustment coefficient, represents a range control coefficient, Θ represents a noise standard deviation of the high-frequency coefficient image, and sgn represents a sign function.

According to the embodiment of the invention, the adaptive threshold value processing is performed on the high-frequency coefficient image obtained by wavelet decomposition, a more suitable processing function is provided for the high-frequency coefficient images under different conditions, and the indexes of the expansion adjustment coefficient, the range control coefficient and the noise standard deviation are also considered, so that noise reduction processing can be performed on noise points in the high-frequency coefficient image comprehensively and accurately, and the subsequent precision of kitchen waste type identification is improved.

In an embodiment, the equalizing the low-frequency coefficient image to obtain an equalized low-frequency coefficient image includes:

carrying out equalization processing on the low-frequency coefficient image by using a global histogram equalization algorithm to obtain a primary processing image cb;

carrying out median filtering processing on the low-frequency coefficient image, and then obtaining an edge image by of the low-frequency coefficient image;

cb and by were fused as follows:

adp＝θ(σ1×cb+σ2×by)

adp represents the low-frequency coefficient image after equalization processing, sigma 1 and sigma 2 are preset fusion weight coefficients, theta represents a control coefficient, and the gray value of a pixel point in the adp is controlled to be in a [0,255] interval.

According to the embodiment of the invention, the low-frequency coefficient image is subjected to median filtering processing firstly, then the edge image is extracted, and the fusion is carried out according to the edge image and the primary processing image, so that the problem that the traditional global histogram equalization algorithm easily causes the loss of image details and edge information can be solved.

In one embodiment, the expansion adjustment coefficient and the range control coefficient are constant type coefficients.

In one embodiment, when k is 1, the neighborhood size of tar is 3 × 3, and the coordinate of tar is (0,0), the coordinates of the neighborhood pixels in the 0-degree direction are (-1,0), (0,0), and (1,0), respectively; the coordinates of the neighborhood pixel points in the 45-degree direction are (-1, -1), (0,0) and (1,1) respectively; the coordinates of the neighborhood pixel points in the 90-degree direction are (0, -1), (0,0) and (0,1) respectively; the coordinates of the neighborhood pixel points in the 135-degree direction are (-1,1), (0,0) and (1, -1), respectively.

In one embodiment, the moving device 4 comprises a universal wheel and a universal wheel locking device for controlling the universal wheel to stop moving.

According to the embodiment of the invention, the garbage can placing frame 3 is moved conveniently by arranging the universal wheels.

In an embodiment, the recognition device 1 further includes a voice obtaining module, the voice obtaining module is used for obtaining voice information of a user about the name of the kitchen waste to be classified, and transmitting the voice information to the recognition module, the recognition module recognizes the voice information, recognizes the name of the kitchen waste to be classified contained in the voice information, obtains the category of the kitchen waste to be classified according to the name, and transmits the category to the display module for displaying.

According to the embodiment of the invention, when the user knows the category of the kitchen waste to be identified, the voice information of the user about the name of the kitchen waste to be identified is directly acquired through the voice acquisition module to identify the name of the kitchen waste to be identified, and then the category of the kitchen waste to be identified is identified according to the name, so that the speed of classifying the kitchen waste can be effectively increased.

In one embodiment, the image acquisition module comprises a camera and a light supplement lamp, the camera is used for acquiring images of the kitchen waste to be classified, and the light supplement lamp is used for providing light for the camera when the light is insufficient.

In one embodiment, the voice acquisition module is a microphone.

From the above description of embodiments, it is clear for a person skilled in the art that the embodiments described herein can be implemented in hardware, software, firmware, middleware, code or any appropriate combination thereof. For a hardware implementation, a processor may be implemented in one or more of the following units: an Application Specific Integrated Circuit (ASIC), a Digital Signal Processor (DSP), a Digital Signal Processing Device (DSPD), a Programmable Logic Device (PLD), a Field Programmable Gate Array (FPGA), a processor, a controller, a microcontroller, a microprocessor, other electronic units designed to perform the functions described herein, or a combination thereof. For a software implementation, some or all of the procedures of an embodiment may be performed by a computer program instructing associated hardware. In practice, the program may be stored on or transmitted over as one or more instructions or code on a computer-readable medium. Computer-readable media includes both computer storage media and communication media including any medium that facilitates transfer of a computer program from one place to another. A storage media may be any available media that can be accessed by a computer. Computer-readable media can include, but is not limited to, RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer.

Finally, it should be noted that the above embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the protection scope of the present invention, 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 can 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.