阅读说明：本技术 目标对象佩戴口罩情况的检测方法及热红外图像处理器 (Method for detecting mask wearing condition of target object and thermal infrared image processor ) 是由 张焱 张华宾 林铭 于 2020-04-26 设计创作，主要内容包括：本申请公开了一种目标对象佩戴口罩情况的检测方法及热红外图像处理器。其中,该方法包括：获取通过热红外图像采集设备采集的第一图像；在第一图像中确定包含目标对象的脸部的第一脸部图像区域；根据第一脸部图像区域的上部图像区域和下部图像区域的图像信息,确定目标对象的上脸部温度信息和下脸部温度信息；以及根据上脸部温度信息和下脸部温度信息,确定目标对象是否佩戴口罩。(The application discloses a method for detecting the mask wearing condition of a target object and a thermal infrared image processor. Wherein, the method comprises the following steps: acquiring a first image acquired by a thermal infrared image acquisition device; determining a first face image region containing a face of the target object in the first image; determining upper face temperature information and lower face temperature information of the target object according to image information of an upper image area and a lower image area of the first face image area; and determining whether the target object wears the mask according to the upper face temperature information and the lower face temperature information.)

1. A method for detecting the mask wearing condition of a target object is characterized by comprising the following steps:

acquiring a first image acquired by a thermal infrared image acquisition device;

determining a first face image region containing a face of a target object in the first image;

determining upper face temperature information and lower face temperature information of the target object according to image information of an upper image area and a lower image area of the first face image area; and

and determining whether the target object wears the mask or not according to the upper face temperature information and the lower face temperature information.

2. A storage medium, characterized in that the storage medium comprises a stored program, wherein the method of claim 1 is performed by a processor when the program is run.

3. A thermal infrared image processor (200), comprising:

an artificial intelligence processing module (220) configured to acquire a first image acquired by a thermal infrared image acquisition device (100) and determine a first face image region containing a face of a target object in the first image;

a temperature detection module (230), connected to the artificial intelligence processing module (220), configured to determine upper face temperature information and lower face temperature information of the target object according to image information of an upper image region and a lower image region of the first face image region; and

a mask wearing condition detection module (240) connected to the temperature detection module (230) and configured to determine whether the target object wears a mask according to the upper face temperature information and the lower face temperature information.

4. The thermal infrared image processor (200) of claim 3, wherein the operation of determining upper face temperature information of the target object comprises:

determining a temperature value corresponding to each pixel of the upper image area; and

and determining the upper face temperature information according to the temperature value corresponding to each pixel.

5. The thermal infrared image processor (200) of claim 3, wherein the operation of determining lower face temperature information of the target object comprises:

determining a temperature value corresponding to each pixel of the lower image area; and

and determining the lower face temperature information according to the temperature value corresponding to each pixel.

6. The thermal infrared image processor (200) of claim 3, wherein the operation of determining whether the target subject is wearing a mask based on the upper face temperature information and the lower face temperature information comprises:

judging whether the temperature difference between the upper face temperature and the lower face temperature of the target object is greater than a preset threshold value or not according to the upper face temperature information and the lower face temperature information; and

and determining whether the target object wears the mask according to the judgment result.

7. The thermal infrared image processor (200) of claim 6, wherein determining whether the target subject is wearing a mask according to a result of the determination comprises:

determining, by the artificial intelligence processing module (220), whether eyes, a nose, and/or a mouth of the target object are included in the first face image region, in a case where a result of the determination is that a temperature difference between an upper face temperature and a lower face temperature of the target object is not greater than a preset threshold;

determining that the target subject wears a mask if the artificial intelligence processing module (220) determines that the first facial image region includes the eyes of the target subject and does not include the nose and/or mouth of the target subject; and

determining that the target subject is not wearing a mask in a case where the artificial intelligence processing module (220) determines that the nose and/or mouth of the target subject is included in the first face image region.

8. The thermal infrared image processor (200) of claim 3, further comprising: the preprocessing module (210) is used for generating a second image corresponding to the first image, wherein the second image is suitable for a preset image detection model to detect; and is

The artificial intelligence processing module (220) comprises a human body part detection unit (221) and a human body part mapping unit (222), wherein

The human body part detection unit (221) is connected with the preprocessing module (210) and is configured to detect a second face image region containing the face of the target object in the second image through the image detection model;

the body part mapping unit (222) is configured to determine the first face image region in the first image based on position information of the second face image region in the second image.

9. The thermal infrared image processor (200) of claim 8, wherein the operation of detecting, by the image detection model, a second face image region in the second image containing the face of the target object, comprises:

detecting a target object image area containing the target object in the second image through the image detection model; and

determining the second face image region in the target object image region.

10. The thermal infrared image processor (200) of claim 8, wherein the pre-processing module (210) comprises at least one of:

a resolution conversion unit (211) configured to convert a resolution of an image into a resolution matching the image detection model; and

an image enhancement unit (212) configured to enhance detail information in the image.

11. The thermal infrared image processor (200) of claim 8, wherein the operation of determining the first face image region in the first image from the position information of the second face image region in the second image comprises:

determining the position information of the first face image area in the first image according to the position information of the second face image area in the second image and the position mapping relation between the first image and the second image; and

and determining the first face image region in the first image according to the position information of the first face image region in the first image.

12. The thermal infrared image processor (200) of claim 3, further comprising an image fusion module (250), connected to the artificial intelligence processing module (220) and the mask worn condition detection module (240), configured to add an identification graphic indicating whether the mask is worn by the target object at a position of the first facial image region.

13. A system for detecting a mask wearing condition of a target object, comprising: a thermal infrared image acquisition device (100); and the thermal infrared image processor (200) of any one of claims 3 to 12, wherein

The thermal infrared image processor (200) is in communication connection with the thermal infrared image acquisition equipment (100) and is used for detecting the mask wearing condition of a target object according to a first image acquired by the thermal infrared image acquisition equipment (100).

14. The system for detecting the mask wearing condition of a target object according to claim 13, further comprising: a display module (310) communicatively coupled to the image fusion module (250) of the thermal infrared image processor (200) for displaying the first image with the added identification graphic.

15. A device for detecting the mask wearing condition of a target object, comprising:

a thermal infrared image acquisition module (510) for acquiring a first image acquired by a thermal infrared image acquisition device;

an image region determination module (520) for determining a first face image region containing a face of a target object in the first image;

a temperature determination module (530) for determining upper face temperature information and lower face temperature information of the target object from image information of an upper image region and a lower image region of the first face image region; and

a mask wearing condition determining module (540) for determining whether the mask is worn by the target object according to the upper face temperature information and the lower face temperature information.

16. A device for detecting the mask wearing condition of a target object, comprising:

a processor (610); and

a memory (620) coupled to the processor (610) for providing instructions to the processor (610) for processing the following processing steps:

acquiring a first image acquired by a thermal infrared image acquisition device;

determining a first face image region containing a face of a target object in the first image;

determining upper face temperature information and lower face temperature information of the target object according to image information of an upper image area and a lower image area of the first face image area; and

and determining whether the target object wears the mask or not according to the upper face temperature information and the lower face temperature information.

Technical Field

The application relates to the technical field of mask detection, in particular to a method for detecting the mask wearing condition of a target object and a thermal infrared image processor.

Background

The mask is a common sanitary article, and can effectively prevent dust, harmful gas, saliva spray and the like from entering and exiting the mouth and the nose. In public places such as offices, shopping malls, hospitals and the like, the mask can be worn to ensure that the mask is not harmed by epidemic of infectious diseases and virus transmission is effectively prevented; the mask is worn in areas with large dust in working environments such as construction sites and factories, and damage to self health caused by dust suction can be prevented. In addition, in some important monitoring places, such as ATM cash dispensers, suspicious people can deliberately cover the face with a mask in order to avoid being captured by a camera. Therefore, in some public places, it is necessary to detect whether or not a mask is worn by a person (target object), that is, whether or not the person wears the mask as required.

The existing detection method for detecting whether related personnel wear the mask as required mostly adopts a manual mode or a mode for detecting whether a target object wears the mask based on a visible light image, but the detection is carried out in a manual mode, so that a large amount of human resources are consumed, and the detection efficiency is low. Whether the mode of wearing gauze mask based on visible light image detection target object is easily influenced by light intensity, for example at night, light intensity is low, and the definition of the visible light image of gathering is not high, leads to unable the detecting or detects the rate of accuracy lower, appears lou examining easily, false retrieval and mistake inspection scheduling problem.

Aiming at the technical problems that the mask wearing condition of the target object is low in detection efficiency and accuracy and easy to cause missed detection, false detection and false detection due to the fact that the manual detection mode needs to consume a large amount of human resources and the mode whether the mask is worn by the target object or not is easily influenced by light intensity based on the mode whether the mask is worn by the manual detection mode or the mode whether the mask is worn by the target object or not is detected by the visible light image in the prior art, an effective solution is not provided at present.

Disclosure of Invention

The utility model provides a detection method and hot infrared image processor that target object wore the gauze mask condition to solve at least the artifical or whether the mode of whether target object wore the gauze mask based on visible light image detection target object who adopts at present among the prior art, because artifical detection mode need consume a large amount of manpower resources and whether the mode of whether the gauze mask was worn to target object based on visible light image detection target object is easily influenced by light intensity, lead to the target object to wear the detection inefficiency of the gauze mask condition, the rate of accuracy is low, cause the technical problem of missed measure, false retrieval and false retrieval easily.

According to an aspect of the embodiments of the present disclosure, there is provided a method for detecting a mask wearing condition of a target object, including: acquiring a first image acquired by a thermal infrared image acquisition device; determining a first face image region containing a face of the target object in the first image; determining upper face temperature information and lower face temperature information of the target object according to image information of an upper image area and a lower image area of the first face image area; and determining whether the target object wears the mask according to the upper face temperature information and the lower face temperature information.

According to another aspect of the embodiments of the present disclosure, there is provided a thermal infrared image processor, including an artificial intelligence processing module configured to acquire a first image acquired by a thermal infrared image acquisition device and determine a first face image region containing a face of a target object in the first image; the temperature detection module is connected with the artificial intelligence processing module and is configured for determining upper face temperature information and lower face temperature information of the target object according to the image information of the upper image area and the lower image area of the first face image area; and a mask wearing condition detection module connected with the temperature detection module and configured to determine whether the target object wears the mask according to the upper face temperature information and the lower face temperature information.

According to another aspect of the embodiments of the present disclosure, there is also provided a system for detecting a mask wearing condition of a target object, including: a thermal infrared image acquisition device; and the thermal infrared image processor, wherein the thermal infrared image processor is in communication connection with the thermal infrared image acquisition device, and is configured to detect a mask wearing condition of a target object for a first image acquired by the thermal infrared image acquisition device.

According to another aspect of the embodiments of the present disclosure, there is also provided an apparatus for detecting a mask wearing condition of a target object, including: the thermal infrared image acquisition module is used for acquiring a first image acquired by thermal infrared image acquisition equipment; an image region determination module for determining a first face image region containing a face of the target object in the first image; a temperature determination module for determining upper face temperature information and lower face temperature information of the target object according to image information of an upper image region and a lower image region of the first face image region; and a mask wearing condition determining module for determining whether the target object wears the mask according to the upper face temperature information and the lower face temperature information.

According to another aspect of the embodiments of the present disclosure, there is also provided an apparatus for detecting a mask wearing condition of a target object, including: a processor; and a memory coupled to the processor for providing instructions to the processor for processing the following processing steps: acquiring a first image acquired by a thermal infrared image acquisition device; determining a first face image region containing a face of the target object in the first image; determining upper face temperature information and lower face temperature information of the target object according to image information of an upper image area and a lower image area of the first face image area; and determining whether the target object wears the mask according to the upper face temperature information and the lower face temperature information.

According to another aspect of the disclosed embodiments, there is also provided a storage medium. The storage medium comprises a stored program, wherein the above described method is performed by a processor when the program is run.

In an embodiment of the present invention, the thermal infrared image processor first acquires a first image acquired by the thermal infrared image acquisition device using the artificial intelligence processing module, and determines a first face image region containing a face of the target object in the first image. By the method, the first face image area only containing the face of the target object can be screened out from the full image picture containing the target detection object, so that the temperature detection of the face of the target object can be conveniently carried out subsequently. Then, the upper face temperature information and the lower face temperature information of the target object are determined from the image information of the upper image area and the lower image area of the first face image area by a temperature detection module connected to the artificial intelligence processing module. Finally, based on the characteristic that the lower face temperature information of the target object wearing the mask is obviously distinguished from the upper face temperature information of the target object, the mask wearing condition detection module can accurately determine whether the target object wears the mask according to the upper face temperature information and the lower face temperature information. Therefore, the hot infrared image processor provided by the application is used for detecting the mask wearing condition based on the hot infrared image, is not influenced by light intensity, is high in detection accuracy, avoids missing detection, false detection and false detection, does not need to consume a large amount of human resources, and greatly improves the detection efficiency. In addition, non-contact detection is carried out by acquiring the first image acquired by the thermal infrared image acquisition equipment, noninductive detection is realized, stopping is not needed, and people flow is quickly dredged. And then solved the artifical mode that whether detects the target object and wear the gauze mask based on the visible light image that adopts at present among the prior art, because artifical detection mode need consume a large amount of manpower resources and whether the mode that whether the gauze mask was worn to the target object based on the visible light image detection easily receives the influence of light intensity, leads to the detection efficiency that the target object wore the gauze mask condition low, and the rate of accuracy is low, causes the technical problem of missed measure, false retrieval and false retrieval easily.

The above and other objects, advantages and features of the present application will become more apparent to those skilled in the art from the following detailed description of specific embodiments thereof, taken in conjunction with the accompanying drawings.

Drawings

Some specific embodiments of the present application will be described in detail hereinafter by way of illustration and not limitation with reference to the accompanying drawings. The same reference numbers in the drawings identify the same or similar elements or components. Those skilled in the art will appreciate that the drawings are not necessarily drawn to scale. In the drawings:

fig. 1 is a schematic diagram of a system for detecting a mask wearing condition of a target object according to embodiment 1 of the present disclosure;

fig. 2 is a schematic view of a first image with an added identification graphic according to embodiment 1 of the present disclosure;

fig. 3 is yet another schematic view of a first image with an added identification graphic according to embodiment 1 of the present disclosure;

fig. 4 is a flowchart of a method for detecting whether a mask is worn by a target object according to a third aspect of embodiment 1 of the present disclosure;

fig. 5 is a schematic diagram of a device for detecting whether a mask is worn by a target object according to embodiment 2 of the present disclosure; and

fig. 6 is a schematic diagram of a device for detecting whether a mask is worn by a target object according to embodiment 3 of the present disclosure.

Detailed Description

It should be noted that, in the present disclosure, the embodiments and features of the embodiments may be combined with each other without conflict. The present disclosure will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.

In order to make the technical solutions of the present disclosure better understood by those skilled in the art, the technical solutions of the embodiments of the present disclosure will be clearly and completely described below with reference to the drawings in the embodiments of the present disclosure, and it is obvious that the described embodiments are only some embodiments of the present disclosure, not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments disclosed herein without making any creative effort, shall fall within the protection scope of the present disclosure.

It should be noted that the terms "first," "second," and the like in the description and claims of the present disclosure and in the above-described drawings are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the terms so used are interchangeable under appropriate circumstances for describing the embodiments of the disclosure herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.

It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments according to the present application. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, and it should be understood that when the terms "comprises" and/or "comprising" are used in this specification, they specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof, unless the context clearly indicates otherwise.