CN116030426A - Big data-based image processing method and system - Google Patents
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- CN116030426A CN116030426A CN202310318263.6A CN202310318263A CN116030426A CN 116030426 A CN116030426 A CN 116030426A CN 202310318263 A CN202310318263 A CN 202310318263A CN 116030426 A CN116030426 A CN 116030426A
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Abstract
The invention is applicable to the technical field of image processing, and provides an image processing method and system based on big data, wherein the method comprises the following steps: collecting production line images, wherein the production line images comprise a plurality of production lines and a plurality of operators, and each production line image is marked with an image number; a corresponding production line template is called according to the image number, a plurality of key areas are determined, and key posts are marked on each key area; performing face recognition on operators in a key area, determining basic information of the operators, judging whether the operators are qualified for being in the key position, and generating first production hidden danger early warning information when the operators are not qualified; and determining wearing protection information according to the key posts, judging whether the corresponding operators meet the wearing protection information, and generating second production hidden danger early warning information when the corresponding operators do not meet the wearing protection information. Therefore, operators at key posts can be automatically supervised in real time, and production safety is guaranteed.
Description
Technical Field
The invention relates to the technical field of image processing, in particular to an image processing method and system based on big data.
Background
The safety production of the factory is crucial, and a plurality of posts in the factory have certain specificity, for example, the personnel who need to wear specific equipment to operate or need to perform operation with certain qualification, if the personnel do not wear specific equipment or do not meet the condition, the operation of the special posts is performed, so that the quality of processed products is influenced, potential safety hazards are caused, and at present, the operation personnel of the special posts are difficult to monitor in real time in the operation process. Therefore, there is a need to provide an image processing method and system based on big data, which aims to solve the above problems.
Disclosure of Invention
Aiming at the defects existing in the prior art, the invention aims to provide an image processing method and system based on big data so as to solve the problems existing in the background art.
The invention is realized in that the method for processing the image based on big data comprises the following steps:
collecting production line images, wherein the production line images comprise a plurality of rows of production lines and a plurality of operators, and each production line image is marked with an image number;
a corresponding production line template is called according to the image number, the production line image is divided into intervals according to the production line template, a plurality of key areas are determined, and key posts are marked on each key area;
performing face recognition on operators in the key area, determining basic information of the operators, judging whether the operators have qualification in the key position according to the basic information of the operators, and generating first production hidden danger early warning information when the operators do not have qualification;
and determining wearing protection information according to the key posts, judging whether the corresponding operators meet the wearing protection information, and generating second production hidden danger early warning information when the corresponding operators do not meet the wearing protection information.
As a further scheme of the invention: the step of calling the corresponding production line template according to the image number specifically comprises the following steps:
inputting the image numbers into a production line template library, wherein the production line template library comprises all the image numbers, and each image number corresponds to one production line template;
outputting a production line template corresponding to the image number, wherein a plurality of key areas are arranged on the production line template, and key posts are marked on each key area.
As a further scheme of the invention: the step of determining the wearing protection information according to the key posts and judging whether the corresponding operation workers meet the wearing protection information or not specifically comprises the following steps:
inputting a key post into a wearing protection library, and outputting wearing protection information corresponding to the key post, wherein the wearing protection information comprises one or more wearing protection images;
and taking the wearing protection image as an identification feature, carrying out feature identification on the image in the key area, and judging whether operators in the key area meet the wearing protection information.
As a further scheme of the invention: the method further comprises the steps of:
determining patrol personnel information according to the acquisition time and the image number, wherein the patrol personnel information comprises a head portrait of the patrol personnel;
identifying an inspection staff in the production line image according to the head images of the inspection staff, determining the position of the inspection staff, and corresponding the position of the inspection staff to each production line image;
integrating the positions of the inspection workers in a plurality of continuous production line images to obtain an inspection worker path.
As a further scheme of the invention: the step of identifying the patrol personnel in the production line image according to the head portraits of the patrol personnel and determining the positions of the patrol personnel specifically comprises the following steps:
identifying the patrol staff in the production line image according to the head portraits of the patrol staff;
calling the position mark characteristics corresponding to each patrol personnel;
the position of the patrol personnel is marked by using the position marking features, and one or more position marking features are corresponding to each production line image.
Another object of the present invention is to provide an image processing system based on big data, the system comprising:
the production line image acquisition module is used for acquiring production line images, wherein the production line images comprise a plurality of production lines and a plurality of operators, and each production line image is marked with an image number;
the key region determining module is used for calling a corresponding production line template according to the image number, dividing the production line image into intervals according to the production line template, determining a plurality of key regions, and marking key posts on each key region;
the first early warning information module is used for carrying out face recognition on operators in the key area, determining basic information of the operators, judging whether the operators have qualification in the key position according to the basic information of the operators, and generating first production hidden danger early warning information when the operators do not have qualification;
and the second early warning information module is used for determining the wearing protection information according to the key posts, judging whether the corresponding operators meet the wearing protection information, and generating second production hidden danger early warning information when the corresponding operators do not meet the wearing protection information.
As a further scheme of the invention: the key region determining module includes:
the image number input unit is used for inputting the image numbers into the assembly line template library, wherein the assembly line template library comprises all the image numbers, and each image number corresponds to one production line template;
the production line template output unit is used for outputting a production line template corresponding to the image number, a plurality of key areas are arranged on the production line template, and key posts are marked on each key area.
As a further scheme of the invention: the second early warning information module comprises:
the wearable protection information unit is used for inputting the key positions into the wearable protection library and outputting wearable protection information corresponding to the key positions, wherein the wearable protection information comprises one or more wearable protection images;
and the image feature recognition unit is used for taking the wearing protection image as a recognition feature, carrying out feature recognition on the image in the key area, and judging whether operators in the key area meet the wearing protection information.
As a further scheme of the invention: the system also comprises a patrol path monitoring module, wherein the patrol path monitoring module specifically comprises:
the inspection personnel information unit is used for determining inspection personnel information according to the acquisition time and the image number, wherein the inspection personnel information comprises an inspection personnel head portrait;
the inspection personnel position unit is used for identifying inspection personnel in the production line images according to the head images of the inspection personnel, determining the positions of the inspection personnel, and each production line image corresponds to the positions of the inspection personnel;
and the patrol personnel path unit is used for integrating the positions of the patrol personnel in the continuous production line images to obtain the patrol personnel path.
As a further scheme of the invention: the patrol personnel position unit comprises:
the inspection personnel identification subunit is used for identifying the inspection personnel in the production line image according to the head portrait of the inspection personnel;
the position mark feature subunit is used for calling the position mark feature corresponding to each patrol personnel;
and the personnel position marking subunit is used for marking the positions of the patrol personnel by using the position marking features, and one or more position marking features are corresponding to each production line image.
Compared with the prior art, the invention has the beneficial effects that:
the invention can carry out face recognition on operators in the key area, determine basic information of the operators, judge whether the operators have qualification in the key position according to the basic information of the operators, and generate first production hidden danger early warning information when the operators do not have qualification; and can confirm according to the key post and dress the protection information, judge whether corresponding operation workman satisfies and dresses the protection information, when not satisfying, generate second production hidden danger early warning information. Therefore, operators at key posts can be automatically supervised in real time, supervision is reliable, and production safety is guaranteed.
Drawings
Fig. 1 is a flowchart of an image processing method based on big data.
Fig. 2 is a flowchart of a method for processing an image based on big data, which calls a corresponding production line template according to an image number.
Fig. 3 is a flowchart for determining whether an operator satisfies wearing protection information in an image processing method based on big data.
Fig. 4 is a flowchart of a method for obtaining a path of a patrol personnel in an image processing method based on big data.
Fig. 5 is a flowchart of determining the position of the patrol personnel in the big data-based image processing method.
Fig. 6 is a schematic diagram of a structure of an image processing system based on big data.
Fig. 7 is a schematic diagram of the structure of a key region determining module in an image processing system based on big data.
Fig. 8 is a schematic structural diagram of a second early warning information module in an image processing system based on big data.
Fig. 9 is a schematic structural diagram of an inspection path inspection module in an image processing system based on big data.
Fig. 10 is a schematic diagram of a structure of a patrol man position unit in an image processing system based on big data.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more clear, the present invention will be described in further detail with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
Specific implementations of the invention are described in detail below in connection with specific embodiments.
As shown in fig. 1, an embodiment of the present invention provides an image processing method based on big data, the method including the steps of:
s100, collecting production line images, wherein the production line images comprise a plurality of drainage pipelines and a plurality of operators, and each production line image is marked with an image number;
s200, a corresponding production line template is called according to the image number, the production line image is divided into intervals according to the production line template, a plurality of key areas are determined, and key posts are marked on each key area;
s300, performing face recognition on operators in a key area, determining basic information of the operators, judging whether the operators have qualification in the key position according to the basic information of the operators, and generating first production hidden danger early warning information when the operators do not have qualification;
s400, determining wearing protection information according to the key posts, judging whether corresponding operators meet the wearing protection information, and generating second production hidden danger early warning information when the corresponding operators do not meet the wearing protection information.
It should be noted that, many posts in the factory have a certain specificity, for example, need to wear specific equipment to perform operations, or need to perform operations by staff with certain qualification, if staff does not wear specific equipment, or does not meet the condition, the operations of the specific posts are performed, which not only affects the quality of processed products, but also causes potential safety hazards, and at present, during the operation, it is difficult to perform real-time supervision on the operators of the specific posts.
In the embodiment of the invention, cameras are required to be installed in a factory, the production line images are acquired in real time through the cameras, each production line image comprises a plurality of production lines and a plurality of operators, each production line image is marked with an image number, the image numbers are in one-to-one correspondence with the cameras, each camera is fixed, so that the position of the production line in the production line image is fixed, then a corresponding production line template is required to be called according to the image numbers, a plurality of key areas are arranged on the production line template, each key area is marked with a key post, the production line template and the production line images are subjected to superposition comparison, and the production line images can be divided into intervals to determine a plurality of key areas; then, face recognition is carried out on operators in the key area, basic information of the operators is determined, an employee information base is established in the factory in advance, the employee information base comprises face images of each employee, and the basic information comprises qualification of which key positions are engaged in, so that whether the operators have qualification of the key positions or not can be judged according to the basic information of the operators, and when the operators do not have qualification, first production hidden danger early warning information is generated; and finally, determining wearing protection information according to the key posts, wherein each key post corresponds to the corresponding wearing protection information, so that whether the corresponding operator meets the wearing protection information or not can be judged, and when the corresponding operator does not meet the wearing protection information, second production hidden danger early warning information is generated. Therefore, operators at key posts can be automatically supervised in real time, supervision is reliable, and production safety is guaranteed.
As shown in fig. 2, as a preferred embodiment of the present invention, the step of retrieving the corresponding production line template according to the image number specifically includes:
s201, inputting image numbers into a pipeline template library, wherein the pipeline template library comprises all the image numbers, and each image number corresponds to one production pipeline template;
s202, outputting a production line template corresponding to the image number, wherein a plurality of key areas are arranged on the production line template, and key posts are marked on each key area.
In the embodiment of the invention, a production line template library is established in advance, the production line template library comprises all image numbers, each image number corresponds to one production line template, a plurality of key areas are arranged on the production line template, each key area is marked with a key post, namely, each camera corresponds to one production line template, the size of the production line template is identical to the size of an image shot by the camera, and the image numbers are input into the production line template library, so that the production line template corresponding to the image numbers can be automatically output.
As shown in fig. 3, as a preferred embodiment of the present invention, the step of determining the wearing protection information according to the key post, and determining whether the corresponding operator meets the wearing protection information specifically includes:
s401, inputting a key post into a wearing protection library, and outputting wearing protection information corresponding to the key post, wherein the wearing protection information comprises one or more wearing protection images;
and S402, taking the wearing protection image as an identification feature, carrying out feature identification on the image in the key area, and judging whether operators in the key area meet the wearing protection information.
In the embodiment of the invention, a wearing protection library is established in advance, the wearing protection library comprises all key posts, each key post corresponds to one piece of wearing protection information, one or more pieces of wearing protection images contained in the wearing protection information are input into the wearing protection library, the corresponding wearing protection information is automatically output, the wearing protection images in the wearing protection information are used as identification features, feature identification is carried out on the images in the key areas, whether operators in the key areas meet the wearing protection information is judged, and when the wearing protection features cannot be identified in the images in the key areas, the operators do not meet the conditions.
As shown in fig. 4, as a preferred embodiment of the present invention, the method further includes:
s501, determining patrol personnel information according to the acquisition time and the image number, wherein the patrol personnel information comprises a head portrait of the patrol personnel;
s502, identifying the inspector in the production line image according to the inspector head portrait, determining the position of the inspector, and corresponding to the position of the inspector in each production line image;
s503, integrating the positions of the inspection workers in a plurality of continuous production line images to obtain an inspection worker path.
In the embodiment of the invention, besides the supervision of operators, the supervision of the patrol personnel of a factory is realized, the information of the patrol personnel is firstly determined according to the acquisition time and the image number, and it is easy to understand that the patrol personnel of each production line are different in each time period, a patrol shift table is established in advance, the image number is bound with the production line, the specific patrol personnel can be determined according to the acquisition time and the image number, then the patrol personnel in the production line image is identified according to the head image of the patrol personnel, the positions of the patrol personnel are determined, and finally, the positions of the patrol personnel in a plurality of continuous production line images are integrated, so that the paths of the patrol personnel can be obtained, and the supervision of the patrol personnel is realized.
As shown in fig. 5, as a preferred embodiment of the present invention, the step of identifying the inspector in the production line image according to the inspector head portrait, and determining the position of the inspector specifically includes:
s5021, identifying patrol personnel in the production line image according to the head portraits of the patrol personnel;
s5022, calling the position mark characteristics corresponding to each patrol personnel;
s5023, marking the position of the patrol personnel by using the position marking features, wherein one or more position marking features are corresponding to each production line image.
In the embodiment of the invention, a plurality of inspection staff may be included in one production line image, in order to avoid the disorder of the paths of the inspection staff, respective position mark features need to be formulated for each inspection staff in advance, for example, the position mark feature of a first inspection staff is a red dot, the position mark feature of a second inspection staff is a yellow dot, and the positions of the inspection staff are marked by using the position mark features, so that one or more position mark features correspond to each production line image.
As shown in fig. 6, an embodiment of the present invention further provides an image processing system based on big data, the system including:
the assembly line image acquisition module 100 is used for acquiring production line images, wherein the production line images comprise a plurality of assembly lines and a plurality of operators, and each production line image is marked with an image number;
the key region determining module 200 is configured to invoke a corresponding production line template according to the image number, partition the production line image according to the production line template, and determine a plurality of key regions, where each key region is marked with a key post;
the first early warning information module 300 is used for carrying out face recognition on operators in a key area, determining basic information of the operators, judging whether the operators have qualification in the key position according to the basic information of the operators, and generating first production hidden danger early warning information when the operators do not have qualification;
and the second early warning information module 400 is used for determining the wearing protection information according to the key posts, judging whether the corresponding operators meet the wearing protection information, and generating second production hidden danger early warning information when the corresponding operators do not meet the wearing protection information.
In the embodiment of the invention, cameras are required to be installed in a factory, the production line images are acquired in real time through the cameras, each production line image comprises a plurality of production lines and a plurality of operators, each production line image is marked with an image number, the image numbers are in one-to-one correspondence with the cameras, each camera is fixed, so that the position of the production line in the production line image is fixed, then a corresponding production line template is required to be called according to the image numbers, a plurality of key areas are arranged on the production line template, each key area is marked with a key post, the production line template and the production line images are subjected to superposition comparison, and the production line images can be divided into intervals to determine a plurality of key areas; then, face recognition is carried out on operators in the key area, basic information of the operators is determined, an employee information base is established in the factory in advance, the employee information base comprises face images of each employee, and the basic information comprises qualification of which key positions are engaged in, so that whether the operators have qualification of the key positions or not can be judged according to the basic information of the operators, and when the operators do not have qualification, first production hidden danger early warning information is generated; and finally, determining wearing protection information according to the key posts, wherein each key post corresponds to the corresponding wearing protection information, so that whether the corresponding operator meets the wearing protection information or not can be judged, and when the corresponding operator does not meet the wearing protection information, second production hidden danger early warning information is generated. Therefore, operators at key posts can be automatically supervised in real time, supervision is reliable, and production safety is guaranteed.
As shown in fig. 7, as a preferred embodiment of the present invention, the critical area determining module 200 includes:
an image number input unit 201, configured to input image numbers into a pipeline template library, where the pipeline template library includes all image numbers, and each image number corresponds to a production pipeline template;
the pipeline template output unit 202 is configured to output a production pipeline template corresponding to the image number, where a plurality of key areas are provided on the production pipeline template, and each key area is marked with a key post.
As shown in fig. 8, as a preferred embodiment of the present invention, the second warning information module 400 includes:
the wearable protection information unit 401 is configured to input a key post into a wearable protection library, and output wearable protection information corresponding to the key post, where the wearable protection information includes one or more wearable protection images;
and an image feature recognition unit 402, configured to perform feature recognition on the image in the key area by using the wearing protection image as a recognition feature, and determine whether the operator in the key area meets the wearing protection information.
As shown in fig. 9, as a preferred embodiment of the present invention, the system further includes a patrol path inspection module 500, where the patrol path inspection module 500 specifically includes:
the inspector information unit 501 is configured to determine inspector information according to the acquisition time and the image number, where the inspector information includes an inspector head portrait;
the inspector position unit 502 is configured to identify inspectors in the production line image according to inspector head images, determine inspector positions, and each production line image corresponds to an inspector position;
and the inspector path unit 503 is configured to integrate the inspector positions in the multiple continuous production line images to obtain an inspector path.
As shown in fig. 10, as a preferred embodiment of the present invention, the patrol personnel location unit 502 includes:
the inspection personnel identification subunit 5021 is used for identifying the inspection personnel in the production line image according to the head portrait of the inspection personnel;
a position mark feature subunit 5022, configured to invoke a position mark feature corresponding to each patrol personnel;
a personnel position marking subunit 5023 configured to mark the position of the patrol personnel using position marking features, one or more position marking features corresponding to each of the production line images.
The foregoing description of the preferred embodiments of the present invention should not be taken as limiting the invention, but rather should be understood to cover all modifications, equivalents, and alternatives falling within the spirit and principles of the invention.
It should be understood that, although the steps in the flowcharts of the embodiments of the present invention are shown in order as indicated by the arrows, these steps are not necessarily performed in order as indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps in various embodiments may include multiple sub-steps or stages that are not necessarily performed at the same time, but may be performed at different times, nor do the order in which the sub-steps or stages are performed necessarily performed in sequence, but may be performed alternately or alternately with at least a portion of the sub-steps or stages of other steps or other steps.
Those skilled in the art will appreciate that all or part of the processes in the methods of the above embodiments may be implemented by a computer program for instructing relevant hardware, where the program may be stored in a non-volatile computer readable storage medium, and where the program, when executed, may include processes in the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the various embodiments provided herein may include non-volatile and/or volatile memory. The nonvolatile memory can include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), memory bus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), among others.
Other embodiments of the present disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure. This application is intended to cover any adaptations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.
Claims (10)
1. An image processing method based on big data, characterized in that the method comprises the following steps:
collecting production line images, wherein the production line images comprise a plurality of rows of production lines and a plurality of operators, and each production line image is marked with an image number;
a corresponding production line template is called according to the image number, the production line image is divided into intervals according to the production line template, a plurality of key areas are determined, and key posts are marked on each key area;
performing face recognition on operators in the key area, determining basic information of the operators, judging whether the operators have qualification in the key position according to the basic information of the operators, and generating first production hidden danger early warning information when the operators do not have qualification;
and determining wearing protection information according to the key posts, judging whether the corresponding operators meet the wearing protection information, and generating second production hidden danger early warning information when the corresponding operators do not meet the wearing protection information.
2. The big data based image processing method according to claim 1, wherein the step of retrieving the corresponding production line template according to the image number specifically comprises:
inputting the image numbers into a production line template library, wherein the production line template library comprises all the image numbers, and each image number corresponds to one production line template;
outputting a production line template corresponding to the image number, wherein a plurality of key areas are arranged on the production line template, and key posts are marked on each key area.
3. The big data based image processing method according to claim 1, wherein the step of determining the wearing protection information according to the key post, and determining whether the corresponding operator satisfies the wearing protection information specifically comprises:
inputting a key post into a wearing protection library, and outputting wearing protection information corresponding to the key post, wherein the wearing protection information comprises one or more wearing protection images;
and taking the wearing protection image as an identification feature, carrying out feature identification on the image in the key area, and judging whether operators in the key area meet the wearing protection information.
4. The big data based image processing method according to claim 1, wherein the method further comprises:
determining patrol personnel information according to the acquisition time and the image number, wherein the patrol personnel information comprises a head portrait of the patrol personnel;
identifying an inspection staff in the production line image according to the head images of the inspection staff, determining the position of the inspection staff, and corresponding the position of the inspection staff to each production line image;
integrating the positions of the inspection workers in a plurality of continuous production line images to obtain an inspection worker path.
5. The method for processing images based on big data according to claim 4, wherein the step of identifying the inspector in the production line image according to the inspector head portrait and determining the position of the inspector specifically comprises the steps of:
identifying the patrol staff in the production line image according to the head portraits of the patrol staff;
calling the position mark characteristics corresponding to each patrol personnel;
the position of the patrol personnel is marked by using the position marking features, and one or more position marking features are corresponding to each production line image.
6. An image processing system based on big data, the system comprising:
the production line image acquisition module is used for acquiring production line images, wherein the production line images comprise a plurality of production lines and a plurality of operators, and each production line image is marked with an image number;
the key region determining module is used for calling a corresponding production line template according to the image number, dividing the production line image into intervals according to the production line template, determining a plurality of key regions, and marking key posts on each key region;
the first early warning information module is used for carrying out face recognition on operators in the key area, determining basic information of the operators, judging whether the operators have qualification in the key position according to the basic information of the operators, and generating first production hidden danger early warning information when the operators do not have qualification;
and the second early warning information module is used for determining the wearing protection information according to the key posts, judging whether the corresponding operators meet the wearing protection information, and generating second production hidden danger early warning information when the corresponding operators do not meet the wearing protection information.
7. The big data based image processing system of claim 6, wherein the key region determination module includes:
the image number input unit is used for inputting the image numbers into the assembly line template library, wherein the assembly line template library comprises all the image numbers, and each image number corresponds to one production line template;
the production line template output unit is used for outputting a production line template corresponding to the image number, a plurality of key areas are arranged on the production line template, and key posts are marked on each key area.
8. The big data based image processing system of claim 6, wherein the second pre-warning information module includes:
the wearable protection information unit is used for inputting the key positions into the wearable protection library and outputting wearable protection information corresponding to the key positions, wherein the wearable protection information comprises one or more wearable protection images;
and the image feature recognition unit is used for taking the wearing protection image as a recognition feature, carrying out feature recognition on the image in the key area, and judging whether operators in the key area meet the wearing protection information.
9. The big data based image processing system of claim 6, further comprising a patrol path inspection module, the patrol path inspection module specifically comprising:
the inspection personnel information unit is used for determining inspection personnel information according to the acquisition time and the image number, wherein the inspection personnel information comprises an inspection personnel head portrait;
the inspection personnel position unit is used for identifying inspection personnel in the production line images according to the head images of the inspection personnel, determining the positions of the inspection personnel, and each production line image corresponds to the positions of the inspection personnel;
and the patrol personnel path unit is used for integrating the positions of the patrol personnel in the continuous production line images to obtain the patrol personnel path.
10. The big data based image processing system of claim 9, wherein the patrol personnel location unit comprises:
the inspection personnel identification subunit is used for identifying the inspection personnel in the production line image according to the head portrait of the inspection personnel;
the position mark feature subunit is used for calling the position mark feature corresponding to each patrol personnel;
and the personnel position marking subunit is used for marking the positions of the patrol personnel by using the position marking features, and one or more position marking features are corresponding to each production line image.
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| CN115630763A (en) * | 2022-10-20 | 2023-01-20 | 上海申雪供应链管理有限公司 | Employee management method and system based on Internet of things |
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| US20210173480A1 (en) * | 2010-02-28 | 2021-06-10 | Microsoft Technology Licensing, Llc | Ar glasses with predictive control of external device based on event input |
| CN108197801A (en) * | 2017-12-29 | 2018-06-22 | 安徽博诺思信息科技有限公司 | Site staff's management method and system and method based on visualized presence monitoring system |
| CN111259682A (en) * | 2018-11-30 | 2020-06-09 | 百度在线网络技术（北京）有限公司 | Method and device for monitoring the safety of a construction site |
| CN115630763A (en) * | 2022-10-20 | 2023-01-20 | 上海申雪供应链管理有限公司 | Employee management method and system based on Internet of things |
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