CN113516062A - Customer identification method and system for automobile repair shop - Google Patents
Customer identification method and system for automobile repair shop Download PDFInfo
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Abstract
The invention provides a customer identification method and a customer identification system for a car repair store, and relates to the technical field of intelligent management of stores. The invention utilizes uniform color information of the work clothes of the automobile repair shop to analyze the clothes color sequence corresponding to the human body joint point before carrying out face recognition so as to distinguish the customers and the workers in the recognition area, and then carries out image enhancement and face recognition on the head images of the customers and finally associates the head images with the customer account numbers. Therefore, compared with the recognition of a large number of characteristic points of the human face, the method can accurately recognize the client only by judging the colors of a small number of regions of the working clothes, avoid performing high-precision data processing on all head images in the recognition region, and realize the reduction of data volume and operation volume in the client recognition process.
Description
Technical Field
The invention relates to the technical field of store intelligent management, in particular to a customer identification method and a customer identification system for an automobile repair store.
Background
When a management system of a car repair shop manages customers, the management system usually needs to acquire face information of the customers so as to better perform marketing application.
When the existing management system for the automobile repair shop performs face recognition, the face recognition and matching are performed after face detection is performed on a high-resolution image of a whole area.
However, in practical implementation of the above method, the requirement of face detection on the resolution of the image is high, which further results in large data amount and computation amount, and causes high cost of operating hardware.
Disclosure of Invention
Technical problem to be solved
Aiming at the defects of the prior art, the invention provides a customer identification method and a customer identification system for an automobile repair shop, and solves the problem that the data volume and the calculation volume are large because the existing automobile repair shop management system carries out face detection on a high-resolution image of a whole area and then carries out face identification and matching when carrying out face identification.
(II) technical scheme
In order to achieve the purpose, the invention is realized by the following technical scheme:
in a first aspect, a customer identification method for a vehicle repair shop is provided, the method comprising:
acquiring an original image of the identification area;
acquiring human body joint point detection information and an image color sequence at a human body joint point which is not a head part on the basis of the original image;
acquiring a garment color sequence corresponding to human body joint points on a work garment of a repair shop;
comparing whether the image color sequence and the garment color sequence are consistent;
if not, acquiring a head image for resolution enhancement;
performing face recognition based on the head image with enhanced resolution to obtain face recognition information;
judging whether a client corresponding to the face identification information is a history client or not based on a cloud server containing face information of the history client;
if not, a new customer account is created and is associated with the face recognition result;
and if so, acquiring the account number of the historical client matched with the face recognition information.
Further, the human joint comprises at least: head, center of spine, left and right shoulders and left and right hips;
the original image comprises a color image and a depth image after registration.
Further, the acquiring a sequence of image colors at a human body joint other than the head based on the original image includes:
acquiring position information of a human body joint point in an original image;
calculating the length information of the client based on the position information of the central spine, the left and right shoulders, the left and right hip joints;
calculating the radius value of each human body joint point based on the length information of the client and the preset length ratio of each human body joint point;
taking the position of the human body joint point as the center of a circle and the radius value of the human body joint point as the radius to obtain the human body joint point image in the original image;
and acquiring a color set in the human body joint point image as an image color sequence at the human body joint point.
Furthermore, the colors of the clothes at the corresponding human body joint points on the work clothes of the automobile repair shop are different;
the color sequence of the clothes of the work clothes of different positions is different.
Further, the comparing whether the image color sequence and the garment color sequence are consistent comprises:
if the color set in the human body joint point image has the color which is the same as the color of the human body joint point in the clothing color sequence, the color of the image of the human body joint point is consistent with the clothing color;
and if the number of the image colors of all the human body joint points consistent with the corresponding clothing colors exceeds a judgment threshold value, the image color sequence is consistent with the clothing color sequence.
Further, the acquiring the head image for resolution enhancement includes:
acquiring the position information of the head in the original image;
calculating a radius value of the head image based on the length information of the client and a preset head-length ratio;
taking the position of the head as the center of a circle and the radius value of the head image as the radius to obtain the head image in the original image;
and performing resolution enhancement on the head image according to the target resolution.
Further, the acquiring the head image for resolution enhancement further comprises:
acquiring a spatial position of a head in the recognition area before acquiring the head image; the spatial location position comprises a three-dimensional coordinate and an orientation;
and acquiring the lighting device closest to the head in the area in front of the client in the identification area for light supplement based on the spatial position.
In a second aspect, there is provided a customer identification system for a car repair shop, the system comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the steps of the above method when executing the computer program.
(III) advantageous effects
The invention provides a customer identification method and a customer identification system for a vehicle repair shop. Compared with the prior art, the method has the following beneficial effects:
the invention utilizes uniform color information of the work clothes of the automobile repair shop to analyze the clothes color sequence corresponding to the human body joint point before carrying out face recognition so as to distinguish the customers and the workers in the recognition area, and then carries out image enhancement and face recognition on the head images of the customers and finally associates the head images with the customer account numbers. Therefore, compared with the recognition of a large number of characteristic points of the human face, the method can accurately recognize the client only by judging the colors of a small number of regions of the working clothes, avoid performing high-precision data processing on all head images in the recognition region, and realize the reduction of data volume and operation volume in the client recognition process.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a flow chart of an embodiment of the present invention;
FIG. 2 is a schematic view of a joint of a human body according to an embodiment of the present invention;
fig. 3 is a schematic diagram of a face feature point according to an embodiment of the invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention are clearly and completely described, and it is obvious that the described embodiments are a part of the embodiments of the present invention, but not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The embodiment of the application provides a customer identification method and a customer identification system for an automobile repair shop, and solves the problem that when the existing automobile repair shop management system carries out face identification, face identification and matching are carried out after face detection is carried out on a high-resolution image of a whole area, so that the data volume and the calculation volume are large.
In order to solve the technical problems, the general idea of the embodiment of the application is as follows: according to the embodiment of the invention, uniform color information of the work clothes of the automobile repair shop is utilized, before face recognition is carried out, a clothes color sequence corresponding to a human body joint point is analyzed to distinguish a client and a worker in a recognition area, then image enhancement and face recognition are carried out on a head image of the client, and finally correlation is carried out with a client account. Therefore, compared with the recognition of a large number of characteristic points of the human face, the embodiment of the invention can accurately recognize the client only by judging the colors of a small number of regions of the working clothes, avoids performing high-precision data processing on all head images in the recognition region, and realizes the reduction of data volume and operation amount in the client recognition process.
In order to better understand the technical solution, the technical solution will be described in detail with reference to the drawings and the specific embodiments.
Example 1:
as shown in fig. 1, the present invention provides a customer identification method for a car repair shop, the method comprising:
acquiring an original image of the identification area;
acquiring human body joint point detection information and an image color sequence at a human body joint point which is not a head part on the basis of the original image;
acquiring a garment color sequence corresponding to human body joint points on a work garment of a repair shop;
comparing whether the image color sequence and the garment color sequence are consistent;
if not, acquiring a head image for resolution enhancement;
performing face recognition based on the head image with enhanced resolution to obtain face recognition information;
judging whether a client corresponding to the face identification information is a history client or not based on a cloud server containing face information of the history client;
if not, a new customer account is created and is associated with the face recognition result;
and if so, acquiring the account number of the historical client matched with the face recognition information.
The beneficial effect of this embodiment does:
according to the embodiment of the invention, uniform color information of the work clothes of the automobile repair shop is utilized, before face recognition is carried out, a clothes color sequence corresponding to a human body joint point is analyzed to distinguish a client and a worker in a recognition area, then image enhancement and face recognition are carried out on a head image of the client, and finally correlation is carried out with a client account. Therefore, compared with the recognition of a large number of characteristic points of the human face, the embodiment of the invention can accurately recognize the client only by judging the colors of a small number of regions of the working clothes, avoids performing high-precision data processing on all head images in the recognition region, and realizes the reduction of data volume and operation amount in the client recognition process.
The following describes the implementation process of the embodiment of the present invention in detail:
s1, acquiring an original image of the identification area;
specifically, the original images may be obtained by an existing human body recognition device, such as kinect, wherein the original images include a color image with a resolution of 640 × 480 and a depth image with a resolution of 320 × 240.
S2, acquiring human body joint point detection information and an image color sequence at a human body joint point which is not a head part based on the original image;
specifically, the joint point identification may also adopt a human body identification device to obtain joint points as shown in fig. 2, and considering the accuracy of the image color sequence and the influence of the bare skin, the human body joint points at least include: six joint points of the head, the center of the spine, the left and right shoulders, and the left and right hips can be added according to actual conditions if further accuracy improvement is needed.
For the image color sequence at the body node other than the head, the size of the body in the image needs to be considered to determine the specific color sampling range, and a feasible step is given as follows, which includes:
s21, acquiring the position information of the human body joint points in the original image;
s22, calculating the length information of the client based on the position information of the central spine, the left and right shoulders and the joint points of the left and right hips;
s23, calculating the radius value of each human body joint point based on the length information of the client and the preset length-to-length ratio of each human body joint point; the human body joint point-length ratio is an empirical value and can be manually acquired and input in advance.
S24, taking the position of the human body joint point as the center of a circle and the radius value of the human body joint point as the radius to obtain the human body joint point image in the original image; this defines the sampling area of the image color sequence.
And S25, acquiring the color set in the human body joint point image as an image color sequence at the human body joint point.
S3, acquiring a clothing color sequence corresponding to human body joint points on a work clothing of the automobile repair shop;
the color sequence of the clothes corresponding to the human body joint points on the work clothes of the automobile repair shop can be manually obtained and input in advance; for example, the corresponding garment color sequences at the center of the spine, left and right shoulders, and left and right hips of the work garment are hexadecimal color codes: (# 0000FF, # F8F8FF, # E6E6FA, #000000, # FFFFFF. RGB color values may also be used.
The working clothes of all the employees can be uniformly matched, and for the uniqueness of the clothes color sequence, the clothes colors at the corresponding human body joint positions on the working clothes of the office repair shop are different;
different color matching can be set according to different work types, namely, the clothes color sequences of the work clothes of different positions are different.
S4, comparing whether the image color sequence is consistent with the clothing color sequence; the method specifically comprises the following steps:
if the color set in the human body joint point image has the color which is the same as the color of the human body joint point in the clothing color sequence, the color of the image of the human body joint point is consistent with the clothing color; considering the color shift of the color image, the same color includes similar colors of the same or similar color, for example, the color is # F8FF (GhostWhite), and the similar colors of the same color include # fffafa (snow), # FFFAF0 (floralbite), and the like, which can be specified by human experience.
And if the number of the image colors of all the human body joint points consistent with the corresponding clothing colors exceeds a judgment threshold value, the image color sequence is consistent with the clothing color sequence. The decision threshold is an empirical value and can be manually input in advance.
S5, if the difference indicates that the identified human body is a client, acquiring a head image for resolution enhancement; if the human body is consistent with the human body, the identified human body is represented as an employee;
to improve the quality of the head image acquisition, the following method may be performed:
acquiring a spatial position of a head in the recognition area before acquiring the head image; the spatial location position comprises a three-dimensional coordinate and an orientation;
and acquiring the lighting device closest to the head in the area in front of the client in the identification area for light supplement based on the spatial position.
When the resolution is enhanced, the range of the face needs to be determined, and therefore, similar to the joint area, the proportional relationship between the length of the face and the head needs to be considered, so the specific steps include:
acquiring the position information of the head in the original image;
calculating a radius value of the head image based on the length information of the client and a preset head-length ratio; the head-length ratio is an empirical value and is manually entered.
Taking the position of the head as the center of a circle and the radius value of the head image as the radius to obtain the head image in the original image;
and performing resolution enhancement on the head image according to the target resolution. The specific parameters of resolution enhancement include magnification factor, and the noise reduction degree can be selectively set according to the requirement.
S6, carrying out face recognition based on the head image with enhanced resolution to obtain face recognition information; the adopted face recognition algorithm needs to detect 68 feature points of the face as shown in fig. 3, and at most hundreds of feature points need to be detected according to the actually required recognition rate.
S7, judging whether the client corresponding to the face recognition information is a history client or not based on the cloud server containing the face information of the history client;
if not, a new customer account is created and is associated with the face recognition result; in specific implementation, the face information of the customer can be stored in the cloud server to realize data sharing of multiple stores, so that a database of the customer management function in the store management system is more complete.
And if so, acquiring the account number of the historical client matched with the face recognition information.
Example 2
The invention also provides a customer identification system for a car repair shop, the system comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the steps of the method when executing the computer program.
It can be understood that the customer identification system for the car department store provided in the embodiment of the present invention corresponds to the customer identification method for the car department store, and the explanation, examples, and beneficial effects of the relevant contents thereof may refer to the corresponding contents in the customer identification method for the car department store, and are not repeated herein.
In summary, compared with the prior art, the invention has the following beneficial effects:
according to the embodiment of the invention, uniform color information of the work clothes of the automobile repair shop is utilized, before face recognition is carried out, a clothes color sequence corresponding to a human body joint point is analyzed to distinguish a client and a worker in a recognition area, then image enhancement and face recognition are carried out on a head image of the client, and finally correlation is carried out with a client account. Therefore, compared with the recognition of a large number of characteristic points of the human face, the embodiment of the invention can accurately recognize the client only by judging the colors of a small number of regions of the working clothes, avoids performing high-precision data processing on all head images in the recognition region, and realizes the reduction of data volume and operation amount in the client recognition process.
It should be noted that, through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by software plus a necessary general hardware platform. With this understanding, the above technical solutions may be embodied in the form of a software product, which may be stored in a storage medium, such as a ROM/RAM, a magnetic disk, an optical disk, etc., and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the method according to the embodiments or some parts of the embodiments. In this document, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
The above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (8)
1. A customer identification method for a car repair shop, the method comprising:
acquiring an original image of the identification area;
acquiring human body joint point detection information and an image color sequence at a human body joint point which is not a head part on the basis of the original image;
acquiring a garment color sequence corresponding to human body joint points on a work garment of a repair shop;
comparing whether the image color sequence and the garment color sequence are consistent;
if not, acquiring a head image for resolution enhancement;
performing face recognition based on the head image with enhanced resolution to obtain face recognition information;
judging whether a client corresponding to the face identification information is a history client or not based on a cloud server containing face information of the history client;
if not, a new customer account is created and is associated with the face recognition result;
and if so, acquiring the account number of the historical client matched with the face recognition information.
2. The customer identification method for a car repair shop as set forth in claim 1, wherein the human body joint points comprise at least: head, center of spine, left and right shoulders and left and right hips;
the original image comprises a color image and a depth image after registration.
3. The customer identification method for the car repair shop as claimed in claim 2, wherein the obtaining of the image color sequence at the human body joint other than the head based on the original image comprises:
acquiring position information of a human body joint point in an original image;
calculating the length information of the client based on the position information of the central spine, the left and right shoulders, the left and right hip joints;
calculating the radius value of each human body joint point based on the length information of the client and the preset length ratio of each human body joint point;
taking the position of the human body joint point as the center of a circle and the radius value of the human body joint point as the radius to obtain the human body joint point image in the original image;
and acquiring a color set in the human body joint point image as an image color sequence at the human body joint point.
4. The customer identification method for the vehicle repair shop as claimed in claim 1, wherein the colors of the clothes at the corresponding human body joint points on the work clothes of the vehicle repair shop are different;
the color sequence of the clothes of the work clothes of different positions is different.
5. The customer identification method for a car repair shop as set forth in claim 1, wherein the comparing whether the image color sequence and the clothing color sequence are identical comprises:
if the color set in the human body joint point image has the color which is the same as the color of the human body joint point in the clothing color sequence, the color of the image of the human body joint point is consistent with the clothing color;
and if the number of the image colors of all the human body joint points consistent with the corresponding clothing colors exceeds a judgment threshold value, the image color sequence is consistent with the clothing color sequence.
6. The customer identification method for a car repair shop as set forth in claim 3, wherein acquiring the head image for resolution enhancement comprises:
acquiring the position information of the head in the original image;
calculating a radius value of the head image based on the length information of the client and a preset head-length ratio;
taking the position of the head as the center of a circle and the radius value of the head image as the radius to obtain the head image in the original image;
and performing resolution enhancement on the head image according to the target resolution.
7. The customer identification method for a car repair shop as set forth in claim 6, wherein the acquiring the head image for resolution enhancement further comprises:
acquiring a spatial position of a head in the recognition area before acquiring the head image; the spatial location position comprises a three-dimensional coordinate and an orientation;
and acquiring the lighting device closest to the head in the area in front of the client in the identification area for light supplement based on the spatial position.
8. A customer identification system for a car repair shop, the system comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor when executing the computer program performs the steps of the method of any one of claims 1 to 7.
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115601606A (en) * | 2022-12-15 | 2023-01-13 | 苏州万店掌软件技术有限公司（Cn） | Store state detection method, device, equipment and storage medium |
Citations (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103003845A (en) * | 2011-03-02 | 2013-03-27 | 松下电器产业株式会社 | Posture estimation device, posture estimation system, and posture estimation method |
| CN104318446A (en) * | 2014-10-17 | 2015-01-28 | 上海和鹰机电科技股份有限公司 | Virtual fitting method and system |
| CN104616018A (en) * | 2014-12-09 | 2015-05-13 | 四川大学 | Improved Hopfield neural network based recognition method for clothes logo |
| CN106162094A (en) * | 2016-08-05 | 2016-11-23 | 北京丰华联合科技有限公司 | A kind of safety in production intelligent video monitoring system for firework factory |
| CN106599781A (en) * | 2016-11-08 | 2017-04-26 | 国网山东省电力公司威海供电公司 | Electric power business hall dressing normalization identification method based on color and Hu moment matching |
| KR20180065441A (en) * | 2016-12-08 | 2018-06-18 | 동국대학교 산학협력단 | Object extraction method and apparatus |
| CN208780809U (en) * | 2017-12-04 | 2019-04-23 | 中建八局第二建设有限公司 | Job site personnel positioning system based on WSN |
| CN110378786A (en) * | 2019-07-29 | 2019-10-25 | 中国工商银行股份有限公司 | Model training method, promise breaking conduction Risk Identification Method, device and storage medium |
| CN110796079A (en) * | 2019-10-29 | 2020-02-14 | 深圳龙岗智能视听研究院 | Multi-camera visitor identification method and system based on face depth features and human body local depth features |
| KR102101332B1 (en) * | 2019-10-11 | 2020-04-16 | 박민식 | Method for idetification worker |
| CN111046360A (en) * | 2019-11-14 | 2020-04-21 | 秒针信息技术有限公司 | Customer information management method and system based on face recognition |
| CN111325806A (en) * | 2020-02-18 | 2020-06-23 | 苏州科达科技股份有限公司 | Clothing color recognition method, device and system based on semantic segmentation |
| CN111325929A (en) * | 2018-12-13 | 2020-06-23 | 阿里巴巴集团控股有限公司 | Store system and data processing method |
| CN112749645A (en) * | 2020-12-30 | 2021-05-04 | 成都云盯科技有限公司 | Garment color detection method, device and equipment based on monitoring video |
-
2021
- 2021-06-24 CN CN202110701549.3A patent/CN113516062B/en active Active
Patent Citations (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103003845A (en) * | 2011-03-02 | 2013-03-27 | 松下电器产业株式会社 | Posture estimation device, posture estimation system, and posture estimation method |
| CN104318446A (en) * | 2014-10-17 | 2015-01-28 | 上海和鹰机电科技股份有限公司 | Virtual fitting method and system |
| CN104616018A (en) * | 2014-12-09 | 2015-05-13 | 四川大学 | Improved Hopfield neural network based recognition method for clothes logo |
| CN106162094A (en) * | 2016-08-05 | 2016-11-23 | 北京丰华联合科技有限公司 | A kind of safety in production intelligent video monitoring system for firework factory |
| CN106599781A (en) * | 2016-11-08 | 2017-04-26 | 国网山东省电力公司威海供电公司 | Electric power business hall dressing normalization identification method based on color and Hu moment matching |
| KR20180065441A (en) * | 2016-12-08 | 2018-06-18 | 동국대학교 산학협력단 | Object extraction method and apparatus |
| CN208780809U (en) * | 2017-12-04 | 2019-04-23 | 中建八局第二建设有限公司 | Job site personnel positioning system based on WSN |
| CN111325929A (en) * | 2018-12-13 | 2020-06-23 | 阿里巴巴集团控股有限公司 | Store system and data processing method |
| CN110378786A (en) * | 2019-07-29 | 2019-10-25 | 中国工商银行股份有限公司 | Model training method, promise breaking conduction Risk Identification Method, device and storage medium |
| KR102101332B1 (en) * | 2019-10-11 | 2020-04-16 | 박민식 | Method for idetification worker |
| CN110796079A (en) * | 2019-10-29 | 2020-02-14 | 深圳龙岗智能视听研究院 | Multi-camera visitor identification method and system based on face depth features and human body local depth features |
| CN111046360A (en) * | 2019-11-14 | 2020-04-21 | 秒针信息技术有限公司 | Customer information management method and system based on face recognition |
| CN111325806A (en) * | 2020-02-18 | 2020-06-23 | 苏州科达科技股份有限公司 | Clothing color recognition method, device and system based on semantic segmentation |
| CN112749645A (en) * | 2020-12-30 | 2021-05-04 | 成都云盯科技有限公司 | Garment color detection method, device and equipment based on monitoring video |
Non-Patent Citations (5)
| Title |
|---|
| FUNAKUBO R等: ""Recognition and handling of clothes with different pattern by dual hand-eyes robotic system"", 《INTERNATIONAL SYMPOSIUM ON SYSTEM INTEGRATION》 * |
| ZHENG X等: ""Color Recognition of clothes based on k-means and mean shift"", 《IEEE INTERNATIONAL CONFERENCE ON 》 * |
| 季晨颖等: ""姿态检测网络在服装关键点检测中的应用"", 《中国科技论文》 * |
| 李华等: ""快速非刚体人体运动三维重建"", 《计算机辅助设计与图形学学报》 * |
| 王茜等: ""利用射频识别技术，追踪客户信息"", 《经营与管理》 * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115601606A (en) * | 2022-12-15 | 2023-01-13 | 苏州万店掌软件技术有限公司（Cn） | Store state detection method, device, equipment and storage medium |
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