CN115359579A - Wisdom attendance management platform based on face identification - Google Patents
Wisdom attendance management platform based on face identification Download PDFInfo
- Publication number
- CN115359579A CN115359579A CN202210873987.2A CN202210873987A CN115359579A CN 115359579 A CN115359579 A CN 115359579A CN 202210873987 A CN202210873987 A CN 202210873987A CN 115359579 A CN115359579 A CN 115359579A
- Authority
- CN
- China
- Prior art keywords
- attendance
- face
- intelligent
- template database
- face recognition
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Classifications
-
- G—PHYSICS
- G07—CHECKING-DEVICES
- G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
- G07C1/00—Registering, indicating or recording the time of events or elapsed time, e.g. time-recorders for work people
- G07C1/10—Registering, indicating or recording the time of events or elapsed time, e.g. time-recorders for work people together with the recording, indicating or registering of other data, e.g. of signs of identity
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/23—Updating
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/27—Replication, distribution or synchronisation of data between databases or within a distributed database system; Distributed database system architectures therefor
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/10—Office automation; Time management
- G06Q10/109—Time management, e.g. calendars, reminders, meetings or time accounting
- G06Q10/1091—Recording time for administrative or management purposes
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
- G06V10/74—Image or video pattern matching; Proximity measures in feature spaces
- G06V10/75—Organisation of the matching processes, e.g. simultaneous or sequential comparisons of image or video features; Coarse-fine approaches, e.g. multi-scale approaches; using context analysis; Selection of dictionaries
- G06V10/751—Comparing pixel values or logical combinations thereof, or feature values having positional relevance, e.g. template matching
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
- G06V10/74—Image or video pattern matching; Proximity measures in feature spaces
- G06V10/761—Proximity, similarity or dissimilarity measures
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/94—Hardware or software architectures specially adapted for image or video understanding
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/16—Human faces, e.g. facial parts, sketches or expressions
- G06V40/161—Detection; Localisation; Normalisation
- G06V40/166—Detection; Localisation; Normalisation using acquisition arrangements
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/16—Human faces, e.g. facial parts, sketches or expressions
- G06V40/168—Feature extraction; Face representation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/40—Spoof detection, e.g. liveness detection
- G06V40/45—Detection of the body part being alive
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Physics & Mathematics (AREA)
- Multimedia (AREA)
- Databases & Information Systems (AREA)
- Business, Economics & Management (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Health & Medical Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Human Resources & Organizations (AREA)
- Oral & Maxillofacial Surgery (AREA)
- Human Computer Interaction (AREA)
- Computing Systems (AREA)
- Software Systems (AREA)
- Data Mining & Analysis (AREA)
- Strategic Management (AREA)
- Evolutionary Computation (AREA)
- Artificial Intelligence (AREA)
- General Engineering & Computer Science (AREA)
- Medical Informatics (AREA)
- Entrepreneurship & Innovation (AREA)
- Economics (AREA)
- Educational Administration (AREA)
- Marketing (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- Tourism & Hospitality (AREA)
- General Business, Economics & Management (AREA)
- Time Recorders, Dirve Recorders, Access Control (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
- Collating Specific Patterns (AREA)
Abstract
The invention discloses an intelligent attendance management platform based on a face recognition algorithm, which comprises an intelligent attendance terminal, wherein the intelligent attendance terminal comprises a high-definition camera and a face recognition system, the high-definition camera detects face images, the face recognition system analyzes and processes the acquired face images, extracts face key characteristic information and sends the face key characteristic information to an edge server; the edge server is used for storing a template database issued by the attendance management system, comparing the key feature information of the human face acquired by the intelligent attendance terminal and sending the comparison result to the attendance management system; and the attendance management system is used for setting attendance management rules, inputting attendance personnel information, establishing a template database, and analyzing and counting the card punching records of attendance personnel passing face identification according to the comparison result output by the edge server. Compared with the prior art, the face recognition method has the advantages of high face recognition accuracy and high attendance management efficiency.
Description
Technical Field
The invention relates to the technical field of office attendance, in particular to an intelligent attendance management platform based on face recognition.
Background
Face recognition is a very popular research area in biometric authentication. The face recognition is favored by people with the advantages of natural and cheap interactive interface, non-contact acquisition, convenient use and the like, and can be applied to access control and attendance checking, system login, entry and exit management, and the contrast of photos of suspects.
For the application of the face recognition technology in the aspect of attendance management, the existing face recognition mode is that a user stands in a specific area of face recognition equipment, the face picture of the user is collected under the conditions of sufficient light, front and stable state, the collected face picture is compared with the data of a face feature template library, the face feature template library is generally specially collected by a specific administrator, the template library is not updated and enriched after the face picture is collected once, the face recognition accuracy of the employee is low, and the normal recognition of the conditions of wearing a mask and the like cannot be realized; the card punching data of the face recognition equipment is independent, needs to be manually exported, is imported into the attendance management system after being processed, and is applied to data statistics, analysis and the like, the manual participation required in the attendance management process is high, and the overall management efficiency is low.
Disclosure of Invention
The invention provides an intelligent attendance management platform based on face recognition, and aims to solve the problems of low face recognition accuracy and low attendance management efficiency in the prior art.
The utility model provides an wisdom attendance management platform based on face identification which characterized in that includes:
the intelligent attendance terminal comprises a high-definition camera and a face recognition system, and the high-definition camera detects a face image; the face recognition system analyzes and processes the collected face image, extracts face key feature information and sends the face key feature information to the edge server;
the edge server is used for storing a template database issued by the attendance management system, comparing the key feature information of the human face collected by the intelligent attendance terminal and sending a comparison result to the attendance management system;
and the attendance management system is used for setting attendance management rules, inputting attendance personnel information, establishing a template database, and analyzing and counting the card punching records of attendance personnel passing face identification according to the comparison result output by the edge server.
Further, the analysis processing process of the face image by the face recognition system comprises living body judgment, judgment of whether the face is shielded, face image processing and face key feature information extraction.
Further, the living body judgment verifies whether the user operates for the real living body himself or herself through blinking and/or mouth opening and/or head shaking and/or head nodding actions.
Further, preprocessing a face image with a non-shielded face and extracting key feature information of the face; and for the face image with the face sheltered, performing Gaussian mask processing and extracting key feature information of the face.
Further, the image preprocessing comprises light compensation, gray level conversion, histogram equalization, normalization, geometric correction, filtering and sharpening of the face image; the key feature information of the human face comprises the local parts of eyes, nose, mouth and chin and the geometrical structure relationship of the local parts.
Furthermore, the template database comprises a standard template database and a special template database, the intelligent attendance terminal sends the key feature information of the face without shielding to the edge server to be compared with the standard template database, and sends the key feature information of the face with shielding to the edge server to be compared with the special template database; after the comparison of the face key characteristic information is passed, the face key characteristic information without shielding is stored in a standard template database, and the face key characteristic information with shielding is stored in a special template database.
Further, the compared key feature information of the human face is stored in the standard template database or the special template database in a block chain mode.
Furthermore, the attendance management system comprises an attendance rule configuration module, an employee information management module, an attendance management module, a leave application module, an organization management module and an attendance statistic module;
the attendance rule configuration module supports custom attendance rules;
the staff information management module supports adding, modifying, deleting and inquiring attendance staff information;
the attendance management module supports attendance result judgment and attendance recording;
the leave-asking application module supports attendance personnel to make a leave-asking application and synchronizes the leave-asking approval result to the attendance management module;
the organization management module supports management of organization information of different companies;
the attendance statistic module supports statistics and query of attendance data of attendance personnel.
Furthermore, the intelligent attendance terminal is connected with a terminal controller, and the terminal controller is connected with an access control management system so as to release attendance checking personnel who pass through face comparison.
Furthermore, intelligence attendance terminal still includes voice prompt module to carry out voice broadcast to attendance personnel's face identification result.
The invention has the beneficial effects that:
(1) By adopting living human face detection, the method can effectively resist deception caused by common means such as photos, videos, face changing, masks, shielding, screen copying and the like, and improves the accuracy rate of human face recognition;
(2) The data comparison process is carried out in the edge server, and the template database is sent to the edge server for processing and control, so that the face identification comparison efficiency is improved;
(3) The invention realizes the sharing of the key characteristic information database data of the face through the block chain, and carries out continuous rich updating, thereby improving the comparison accuracy.
(4) The invention adopts a front-end and back-end integrated scheme, the data of the attendance management system can be directly called and shared, and the working efficiency and the accuracy of attendance management personnel are greatly simplified.
Drawings
Fig. 1 is a system architecture diagram of an embodiment of an intelligent attendance management platform based on face recognition;
fig. 2 is a flowchart of an embodiment of an intelligent attendance management platform based on face recognition.
Detailed Description
To facilitate an understanding of the invention, the invention will now be described more fully with reference to the accompanying drawings. Preferred embodiments of the present invention are shown in the drawings. This invention may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used herein, the term "and/or" includes any and all combinations of one or more of the associated listed items.
Example one
Referring to fig. 1, fig. 1 is a system architecture diagram of a first embodiment of the present invention, as shown in fig. 1, a smart attendance management platform based on face recognition includes an intelligent attendance terminal, an edge server, and an attendance management system, where the intelligent attendance terminal is connected to the edge server, and the edge server is connected to the attendance management system; the intelligent attendance checking terminal collects face images of attendance checking personnel, analyzes and processes the face images, extracts face key feature information and sends the face key feature information to the edge server; the edge server acquires a template database from the attendance management system in real time, compares the face key feature information sent by the intelligent attendance terminal with the template database, and sends a comparison result to the attendance management system; and the attendance management system records and compares the passing attendance punching information of the attendance personnel, and analyzes and counts the attendance punching information.
Specifically, intelligence attendance terminal includes high definition digtal camera and face identification system.
The high definition digtal camera gathers attendance personnel's face image, and when attendance personnel was in high definition digtal camera's shooting scope, high definition digtal camera automatic search and shot attendance personnel's face image.
The face recognition system analyzes and processes the face image, and the analyzing and processing process comprises living body judgment, face shielding judgment, face image processing and face key feature information extraction.
After the high-definition camera detects the face, the face recognition system firstly carries out living body judgment, screens and removes deception behaviors such as pictures, videos and masks, and the living body judgment verifies whether attendance checking personnel operate as a real living body by blinking and/or opening the mouth and/or shaking and/or nodding the head through face key point positioning and face tracking technologies.
If the living body detection does not pass, the intelligent attendance terminal displays an interface prompt to quit after the prompt is 'please try again, and the employee is required to operate himself'.
If the living body detection is passed, the face recognition system continuously judges whether the face of the attendance personnel is shielded, such as wearing a mask or sunglasses.
If the image is not shielded, preprocessing the face image and extracting key feature information of the face;
the face image preprocessing mainly comprises light compensation, gray level conversion, histogram equalization, normalization, geometric correction, filtering, sharpening and the like of the face image.
If the occlusion exists, the face image is subjected to Gaussian mask processing, and then key feature information of the face is extracted.
The key feature information of the human face comprises the parts of eyes, nose, mouth and chin and the geometrical structure relationship thereof.
Specifically, the edge server stores a template database issued by the backup attendance management system, wherein the template database comprises a standard template database and a special template database, the face recognition system sends face key feature information data of which the face is not shielded to the edge server and compares the face key feature information data with the face, and the edge server compares the face key feature information data with the face, which is shielded, with the data of the special template database, and the specific method comprises the following steps:
presetting a threshold value;
matching the key feature information data of the human face with feature template information data in a template database, and outputting a compared similarity value;
when the similarity value exceeds a threshold value, outputting a comparison result as 'pass';
and when the similarity value does not exceed the threshold value, otherwise, outputting a comparison result as 'failed', and prompting 'please re-detect'.
Specifically, the face key feature information data with the comparison result of 'pass' is stored in a template database in a block chain mode, wherein the face key feature information data without shielding is stored in a standard template database, the face key feature information data with shielding is stored in a special template database, the data of the standard template database and the special template database are continuously updated abundantly, and the edge server backs up the data of the standard template database and the special template database in real time.
Specifically, the attendance management system is used for setting attendance management rules, inputting attendance personnel information, establishing a template database, and analyzing and counting the card punching records of attendance personnel passing face identification according to a comparison result output by the edge server; the attendance management system comprises an attendance rule configuration module, an employee information management module, an attendance management module, a leave-asking application module, an organization management module and an attendance statistic module.
The attendance rule configuration module supports a user to carry out attendance rule self-defined configuration, rule indexes of late arrival, early departure, leave asking and absenteeism are preset in the module, and normal attendance or abnormal attendance on the day is automatically judged according to attendance checking personnel card punching data.
The staff information management module supports unified management on attendance staff information, and supports addition, modification, deletion and staff information query.
The attendance management module supports management of attendance records of attendance personnel, combines the attendance rule configuration module and the leave-on application module, and supports attendance records, attendance result judgment and attendance data query.
The leave-asking application module supports attendance checking personnel to propose leave-asking applications, including annual leave, sick leave, accident leave, wedding leave, parturient leave, rest, industrial injury leave, legal leave, mourish leave and the like.
The organization management module supports management of organization information of different companies, can add, delete, modify and query the organization information, provides different organization architectures of a group, a company and a subsidiary company, is associated with the staff information management module, can directly call and select the organization information when attendance staff information is input, and reduces the input workload of an administrator.
The attendance statistical module supports automatic generation of attendance daily statistical reports, monthly statistical reports and department statistical reports according to the data of the attendance management module, and displays the statistical results in the form of charts and graphs, so that users can conveniently check the data.
In other embodiments, the intelligent attendance terminal is connected with the terminal controller, the terminal controller is connected with the access control system, when the face data comparison is passed, the edge server sends an instruction to the terminal controller, and the terminal controller controls the access control system to release attendance personnel.
In other embodiments, the intelligent attendance terminal is also provided with a voice prompt module to carry out voice broadcast on the face recognition result of the attendance personnel.
Referring to fig. 2, fig. 2 is a system flowchart according to a first embodiment of the present invention, and as shown in fig. 2, a workflow of an intelligent attendance management platform based on face recognition includes:
s10, setting attendance management rules, inputting attendance personnel information, and establishing a template database, wherein the method specifically comprises the following steps:
s11, setting attendance management rules in an attendance rule configuration module, wherein the attendance management rules comprise time parameters such as late arrival, early departure, leave-on, absence and the like; the organization management module is used for inputting organization information of attendance checking personnel, wherein the organization information comprises enterprise names and functional departments; the method comprises the steps that attendance information is input into an employee information management module, the attendance information comprises a name and a job number, and the employee information management module automatically calls organization information of an organization management module;
s12, recording the non-shielding face data of the attendance personnel in the intelligent attendance terminal, and storing the data into a standard template database and a special template database in a block chain mode;
and S13, the edge server acquires the data of the standard template database and the special template database in real time.
S20, the intelligent attendance checking terminal detects a face, the face recognition system analyzes and processes a face image and acquires key feature information of the face, and the method specifically comprises the following steps:
s21, detecting a human face by a high-definition camera of the intelligent attendance checking terminal, and judging the living body;
the face recognition system mainly adopts blinking and/or mouth opening and/or head shaking and/or head nodding actions to judge whether the attendance personnel are living bodies, and can effectively resist deception behaviors caused by common means such as photos, videos, face changing, masks, sheltering and screen copying.
If the living body is not the living body, prompting that the employee operates the living body again, and ending the detection process;
if the living body is present, the next step is performed.
S22, judging whether the detected living face is shielded or not by the face recognition system, processing the face image and extracting key feature information of the face;
if the face is not shielded, preprocessing the face image, positioning coordinates of key parts of the face, and extracting key feature information of the face;
if the face is shielded, processing the face image by adopting a Gaussian mask method, and extracting key feature information of the face.
And S23, sending the extracted key feature information data of the human face to an edge server.
S30, the edge server compares the detected face key feature information data with data of a template database and outputs a comparison result, and the method specifically comprises the following steps:
s31, a similarity threshold value is preset by the face recognition system, and the threshold value is sent to an edge server;
s32, comparing the extracted key feature information data of the human face with a template database:
comparing the key feature information of the human face without the face shield with a standard template database, and outputting a similarity value;
and comparing the key feature information of the face with the shielding face with a special template database, and outputting a similarity value.
And S33, outputting a comparison result.
When the similarity value does not exceed the threshold value, the comparison result is 'failed', the prompt 'please re-detect' is prompted, and the step S20 is returned;
and when the similarity value exceeds the threshold value, outputting a comparison result as 'pass', and entering the next step.
And S34, the edge server stores the face key feature information data with the comparison result of 'pass' to a template database in a block chain mode, wherein the face key feature information data without shielding are stored to a standard template database, and the face key feature information data with shielding are stored to a special template database.
S40, the edge server sends the attendance data of the checked-in personnel passing through the comparison to an attendance management system, and the attendance management system analyzes and counts the attendance data, and the method specifically comprises the following steps:
s41, the attendance management module judges whether the comparison and identification is carried out for the first time in the day;
if the comparison and identification are carried out for the first time on the same day, prompting that the card punching is successful, recording the name, the work number and the card punching time of an attendance person, and automatically recording the card punching time as the attendance starting point time by an attendance management module;
if the comparison identification is not the first comparison identification on the same day, the next step is carried out.
S42, the attendance management module judges whether the comparison and identification is carried out for the last time in the day:
if the last comparison and identification are carried out on the same day, prompting that the card punching is successful, recording the name, the job number and the card punching time of the attendance personnel, and automatically recording the card punching time as the attendance terminal time by the attendance management module;
if the current time is not the last time of comparison and identification in the current day, prompting that the card punching is successful, and recording the name, the job number and the card punching time of the attendance personnel.
And S43, the attendance statistic module summarizes attendance data of the attendance personnel and outputs attendance statistic results.
The attendance statistics module calls the leave-asking application module and the attendance management module to count and summarize the employee attendance data, generates an attendance day statistics report, a month statistics report, a department statistics report and a company statistics report, and displays the statistics result in a chart and graph form, so that a user can conveniently view the data.
While the preferred embodiments of the present invention have been illustrated and described, it will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (10)
1. The utility model provides an wisdom attendance management platform based on face identification which characterized in that includes:
the intelligent attendance terminal comprises a high-definition camera and a face recognition system, and the high-definition camera detects a face image; the face recognition system analyzes and processes the collected face image, extracts face key feature information and sends the face key feature information to the edge server;
the edge server is used for storing a template database issued by the attendance management system, comparing the key feature information of the human face acquired by the intelligent attendance terminal and sending the comparison result to the attendance management system;
and the attendance management system is used for setting attendance management rules, inputting attendance personnel information, establishing a template database, and analyzing and counting the card punching records of attendance personnel passing face identification according to the comparison result output by the edge server.
2. The intelligent attendance management platform based on face recognition as claimed in claim 1, wherein the analysis and processing process of the face image by the face recognition system comprises living body judgment, judgment of whether the face is occluded, face image processing and face key feature information extraction.
3. The intelligent attendance management platform based on face recognition as claimed in claim 2, wherein the living body judgment verifies whether the user is a real living body operation by blinking and/or opening mouth and/or shaking and/or nodding head.
4. The intelligent attendance management platform based on face recognition according to claim 3, wherein the face image without face occlusion is preprocessed to extract key feature information of the face; and for the face image with the face sheltered, carrying out Gaussian mask processing and then extracting face key feature information.
5. The intelligent attendance management platform based on face recognition as claimed in claim 4, wherein the image preprocessing comprises light compensation, gray scale transformation, histogram equalization, normalization, geometric correction, filtering and sharpening of the face image; the key feature information of the human face comprises the local parts of eyes, nose, mouth and chin and the geometrical structure relationship of the local parts.
6. The intelligent attendance management platform based on face recognition as claimed in claim 1, wherein the template database comprises a standard template database and a special template database, the intelligent attendance terminal sends the key feature information of the face without occlusion to the edge server for comparison with the standard template database, and sends the key feature information of the face with occlusion to the edge server for comparison with the special template database; and after the comparison of the face key characteristic information is passed, storing the face key characteristic information without shielding into a standard template database, and storing the face key characteristic information with shielding into a special template database.
7. The intelligent attendance management platform based on face recognition as claimed in claim 6, wherein the compared face key feature information is stored in the standard template database or the special template database in a block chain manner.
8. The intelligent attendance management platform based on face recognition as claimed in claim 1, wherein the attendance management system comprises an attendance rule configuration module, an employee information management module, an attendance management module, an ask for leave application module, an organization management module, and an attendance statistics module;
the attendance rule configuration module supports custom attendance rules;
the staff information management module supports adding, modifying, deleting and inquiring attendance staff information;
the attendance management module supports attendance result judgment and attendance recording;
the leave-asking application module supports attendance checking personnel to make leave-asking applications and synchronizes leave-asking examination and approval results to the attendance checking management module;
the organization management module supports management of organization information of different companies;
the attendance statistic module supports statistics and query of attendance data of attendance personnel.
9. The intelligent attendance management platform based on face recognition as claimed in claim 1, wherein the intelligent attendance terminal is connected with a terminal controller, and the terminal controller is connected with an access control management system to allow attendance checking personnel who pass face comparison to pass.
10. The intelligent attendance management platform based on face recognition as claimed in claim 1, wherein the intelligent attendance terminal further comprises a voice prompt module to perform voice broadcast of the face recognition result of the attendance personnel.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210873987.2A CN115359579A (en) | 2022-07-25 | 2022-07-25 | Wisdom attendance management platform based on face identification |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210873987.2A CN115359579A (en) | 2022-07-25 | 2022-07-25 | Wisdom attendance management platform based on face identification |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN115359579A true CN115359579A (en) | 2022-11-18 |
Family
ID=84032808
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210873987.2A Pending CN115359579A (en) | 2022-07-25 | 2022-07-25 | Wisdom attendance management platform based on face identification |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115359579A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN118450434A (en) * | 2024-04-24 | 2024-08-06 | 北京宜通华瑞科技有限公司 | RFID intelligent interaction device and method |
| CN118586884A (en) * | 2024-06-21 | 2024-09-03 | 中国农业银行股份有限公司江苏省分行 | A visual management platform for intelligent attendance system |
-
2022
- 2022-07-25 CN CN202210873987.2A patent/CN115359579A/en active Pending
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN118450434A (en) * | 2024-04-24 | 2024-08-06 | 北京宜通华瑞科技有限公司 | RFID intelligent interaction device and method |
| CN118450434B (en) * | 2024-04-24 | 2024-11-05 | 北京宜通华瑞科技有限公司 | RFID intelligent interaction device and method |
| CN118586884A (en) * | 2024-06-21 | 2024-09-03 | 中国农业银行股份有限公司江苏省分行 | A visual management platform for intelligent attendance system |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US8803975B2 (en) | Interactive system for recognition analysis of multiple streams of video | |
| US8340366B2 (en) | Face recognition system | |
| DE102013102399B4 (en) | Facial feature detection | |
| CN112199530B (en) | Multi-dimensional face library picture automatic updating method, system, equipment and medium | |
| CN110705482A (en) | Personnel behavior alarm prompt system based on video AI intelligent analysis | |
| CN111126219A (en) | An artificial intelligence-based identification system and method for substation personnel | |
| CN115359579A (en) | Wisdom attendance management platform based on face identification | |
| CN106997629A (en) | Access control method, apparatus and system | |
| CN111914742A (en) | Attendance checking method, system, terminal equipment and medium based on multi-mode biological characteristics | |
| US20210264374A1 (en) | Time monitoring system | |
| CN111353338A (en) | Energy efficiency improvement method based on business hall video monitoring | |
| CN109508685A (en) | Power communication dispatching method based on face recognition technology | |
| CN105868693A (en) | Identity authentication method and system | |
| CN111522974A (en) | Real-time filing method and device | |
| CN111800428A (en) | Real-time statistical method and system for digital conference participation | |
| CN114420302A (en) | Intelligent epidemic prevention control system for enterprises and public institutions | |
| US20140072184A1 (en) | Automated image identification method | |
| CN111027937A (en) | Attendance system | |
| CN114358993A (en) | Full-flow digital archive system based on face recognition | |
| CN108734144A (en) | A kind of speaker's identity identifying method based on recognition of face | |
| CN110287841B (en) | Image transmission method and apparatus, image transmission system, and storage medium | |
| CN113591619A (en) | Face recognition verification device based on video and verification method thereof | |
| CN209086960U (en) | A kind of intelligent image identifying system | |
| CN113128452A (en) | Greening satisfaction acquisition method and system based on image recognition | |
| CN211454668U (en) | Enterprise employee attendance system |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |