CN111339939B - Attendance checking method and device based on image recognition - Google Patents
Attendance checking method and device based on image recognition Download PDFInfo
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Abstract
The invention discloses an attendance checking method and device based on image recognition, wherein the method comprises the following steps: obtaining attendance data to be processed, wherein the attendance data comprises: a collective image containing a plurality of user face images and corresponding activity information; preprocessing the collective image and identifying a face image in the collective image; performing matching operation according to the activity information and the identified face image and pre-stored activity registration information, wherein the activity registration information comprises: user information and face images of users needing to participate in activities; and identifying whether the user needing to participate in the activity participates in the activity or not according to the matching operation result so as to generate attendance result data. According to the invention, the user does not need to queue in sequence to finish the attendance record, the noninductive experience is better, and the attendance statistics is finished manually, so that the efficiency is higher.
Description
Technical Field
The invention relates to the field of image processing, in particular to an attendance checking method and device based on image recognition.
Background
Attendance management is an important means for ensuring that each activity, training and course organization party manages the teaching process of a student and maintains the normal teaching order. In the traditional attendance mode at present, the attendance is usually carried out by means of active triggering (such as signing and roll calling) of an entity card or a student, and the attendance is sequentially and one by one in a queuing way, so that the attendance cost and time are increased, and the condition of poor noninductive experience is caused. The organization side needs to consume a certain amount of manpower and time cost to process the attendance data, has the defects of low timeliness, scattered information and easy error leakage, and also has the influence of low efficiency and inaccurate statistical analysis on teaching management work to a certain extent.
Disclosure of Invention
In view of the above, the present invention provides an attendance checking method and device based on image recognition to solve at least one of the above mentioned problems.
According to a first aspect of the present invention, there is provided an attendance method based on image recognition, the method comprising: obtaining attendance data to be processed, wherein the attendance data comprises: a collective image containing a plurality of user face images and corresponding activity information; preprocessing the collective image and identifying a face image in the collective image; performing matching operation according to the activity information and the identified face image and pre-stored activity registration information, wherein the activity registration information comprises: user information and face images of users needing to participate in activities; and identifying whether the user needing to participate in the activity participates in the activity or not according to the matching operation result so as to generate attendance result data.
According to a second aspect of the present invention, there is provided an attendance device based on image recognition, the device comprising: the data acquisition unit is used for acquiring the attendance data to be processed, and the attendance data comprises: a collective image containing a plurality of user face images and corresponding activity information; the image recognition unit is used for preprocessing the collective image and recognizing a face image in the collective image; a matching unit, configured to perform a matching operation according to the activity information and the identified face image, and pre-stored activity registration information, where the activity registration information includes: user information and face images of users needing to participate in activities; and the identification unit is used for identifying whether the user needing to participate in the activity participates in the activity according to the matching operation result so as to generate attendance result data.
According to a third aspect of the present invention, there is provided an electronic device 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 image recognition based attendance method when executing the program.
According to a fourth aspect of the present invention there is provided a computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of the above image recognition based attendance method.
According to the technical scheme, the collective images in the obtained attendance data are identified to obtain the face images of each user, and the face images are matched based on the pre-stored activity registration information, so that attendance result data are generated.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of an attendance method based on image recognition according to an embodiment of the present invention;
FIG. 2 is a block diagram of an attendance device based on image recognition according to an embodiment of the present invention;
fig. 3 is a block diagram of the structure of the image recognition unit 22 according to the embodiment of the present invention;
FIG. 4 is a detailed block diagram of an attendance device based on image recognition according to an embodiment of the present invention;
fig. 5 is a block diagram of the configuration of the matching unit 23 according to the embodiment of the present invention;
FIG. 6 is an exemplary block diagram of a face image based attendance system in accordance with an embodiment of the present invention;
fig. 7 is a block diagram of the information registration entry platform 1 according to an embodiment of the present invention;
fig. 8 is a block diagram of the face image processing system 2 according to the embodiment of the present invention;
FIG. 9 is a block diagram of the data statistics analysis platform 3 according to an embodiment of the present invention;
FIG. 10 is a flow chart of initial information registration entry based on the system shown in FIG. 6, in accordance with an embodiment of the present invention;
FIG. 11 is a flow chart of face image matching and recognition based on the system of FIG. 6, in accordance with an embodiment of the present invention;
FIG. 12 is a flow chart of a statistical analysis of attendance data based on the system of FIG. 6 in accordance with an embodiment of the present invention;
fig. 13 is a schematic diagram of an electronic device according to an embodiment of the invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments of the present invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
In view of the problems of poor noninductive experience, labor consumption, time analysis and statistics and the like of the existing attendance checking mode, the embodiment of the invention provides an attendance checking scheme based on image recognition to solve the problems.
Fig. 1 is a flowchart of an attendance checking method based on image recognition according to an embodiment of the present invention, as shown in fig. 1, the method includes:
step 101, obtaining attendance data to be processed, wherein the attendance data comprises: a collective image containing a plurality of user face images and corresponding activity information.
Preferably, the collective image can be acquired through the image pickup device, so that the user's noninductive experience is improved.
And 102, preprocessing the collective image and identifying a face image in the collective image.
Specifically, face feature extraction operations may be performed on the preprocessed collective images based on the parallel processing mode to identify face images therein.
Step 103, performing matching operation according to the activity information and the identified face image and pre-stored activity registration information, wherein the activity registration information comprises: user information and face images of users who need to participate in activities.
And step 104, identifying whether the user needing to participate in the activity participates in the activity according to the matching operation result so as to generate attendance result data.
By identifying collective images in the obtained attendance data to obtain face images of each user and carrying out matching operation on a plurality of face images based on pre-stored activity registration information, attendance result data are generated.
In actual operation, when a user needs to participate in a plurality of different activities, the activity registration information can be classified based on a trained classification model; and generates the activity registration information with the activity information as a category according to the classification processing result.
For example, for a teaching work, a learner may participate in a plurality of courses, and thus, activity registration information may be generated based on the courses as categories, and correspondence between the courses, the learner, and face images thereof may be established.
The classification model may be a KNN (K-nearest neighbor algorithm, K-Nearest Neighbors) model.
For the matching operation in step 103, the activity registration information of the corresponding category may be determined according to the activity information, and then the matching operation may be performed on the identified face image based on the traversal loop mechanism according to the determined activity registration information of the corresponding category.
After the attendance is completed, attendance result data can be counted according to a preset rule by using activity information or user information so as to facilitate later checking and counting.
Based on similar inventive concepts, the embodiment of the invention also provides an attendance checking device based on image recognition, which is preferably used for realizing the flow in the embodiment of the method.
Fig. 2 is a block diagram of an attendance device based on image recognition according to an embodiment of the present invention, as shown in fig. 2, the device includes: a data acquisition unit 21, an image recognition unit 22, a matching unit 23, and an identification unit 24, wherein:
a data acquisition unit 21, configured to acquire attendance data to be processed, where the attendance data includes: a collective image containing a plurality of user face images and corresponding activity information. Specifically, a collective image of users participating in an activity can be acquired through the image pickup device, so that the image of the users can be acquired without sense.
An image recognition unit 22, configured to preprocess the collective image and recognize a face image therein.
A matching unit 23 for performing a matching operation with pre-stored event registration information according to the event information and the recognized face image, the event registration information including: user information and face images of users who need to participate in activities.
And the identification unit 24 is used for identifying whether the user needing to participate in the activity participates in the activity according to the matching operation result so as to generate attendance result data.
The image recognition unit 22 recognizes the collective images in the attendance data acquired by the data acquisition unit 21 to obtain face images of each user, the matching unit 23 performs matching operation on the face images based on the pre-stored activity registration information, and the identification unit 24 generates attendance result data according to the matching result.
Specifically, as shown in fig. 3, the image recognition unit 22 includes: a preprocessing module 221 and an image recognition module 222, wherein:
a preprocessing module 221, configured to preprocess the collective image;
The image recognition module 222 is configured to perform a face feature extraction operation on the preprocessed collective image based on the parallel processing mode, so as to recognize a face image therein.
In actual operation, as shown in fig. 4, the apparatus further includes: a classification unit 25 and an activity registration information generation unit 26, wherein:
a classification unit 25, configured to classify the activity registration information based on a trained classification model when a user needs to participate in a plurality of different activities;
an activity registration information generating unit 26 for generating activity registration information classified into activity information based on the classification processing result.
Specifically, as shown in fig. 5, the matching unit 23 includes: an activity registration information determination module 231 and a matching module 232, wherein:
an activity registration information determining module 231 for determining activity registration information of a corresponding category according to the activity information;
and the matching module 232 is used for performing matching operation on the identified face images based on the traversal circulation mechanism according to the determined activity registration information of the corresponding category.
With continued reference to fig. 4, the apparatus further includes: a statistics unit 27 for counting attendance result data with activity information or with user information according to a predetermined rule.
The specific execution process of each unit and each module may be referred to the description in the above method embodiment, and will not be repeated here.
For a better understanding of the embodiments of the present invention, the following describes the embodiments of the present invention in detail in connection with a teaching scenario.
Fig. 6 is an exemplary block diagram of an attendance system based on a face image according to an embodiment of the present invention, as shown in fig. 6, the system comprising: the system comprises an information registration and input platform 1, a face image processing system 2 and a data statistics and analysis platform 3. Preferably, the face image processing system 2 has the function of the above-mentioned attendance checking device. The information registration and input platform 1 can be connected with the face image processing system 2 through a mobile or wired network, and the data statistics analysis platform 3 is in communication connection with the information registration and input platform 1 and the face image processing system 2.
The information registration and input platform 1 is responsible for interaction with operators and the face image processing system 2, and teaching information, face image acquisition, attendance checking request and result receiving. The information registration and input platform provides a visual interaction interface for operators based on a Web browsing and mobile intelligent device mode, wherein the mobile intelligent device comprises, but is not limited to, a mobile phone and a tablet computer, and the interaction mode comprises, but is not limited to, a mode of being aroused by a camera of the mobile intelligent device and inputting H5 (Web page of a mobile terminal) page information.
The face image processing system 2 is responsible for preprocessing, positioning and cutting, feature extraction, classification training, matching, recognition and the like of the received face image.
In response to the initial information registration entry, the face image processing system 2 performs preprocessing such as normalization, light enhancement/attenuation, geometric correction, gray scale conversion adjustment and the like on the face image by using an image processing algorithm, and then performs positioning cutting on the face involved in the image according to a predetermined positioning cutting algorithm, wherein the positioning cutting algorithm mainly judges whether the face exists, the size, the range and the like of the face, so that the calculation amount and the processing time are reduced when the face features are extracted later. The embodiment of the invention can extract the characteristic value of the face image by adopting an EigenFaces algorithm based on PCA (Principal Components Analysis, principal component analysis), and then generate a folder according to a unique identification code (including but not limited to a mobile phone number, a school number and an identity card ID) of a single student and a name, wherein the face image of the student is stored in the folder. Meanwhile, binding relations are established among teaching classes, personnel information and face characteristic values in the system, and corresponding classifiers are generated for dimensions according to the teaching classes. And simultaneously, returning the face image processing result to an information registration and input platform, and transmitting course information to a data statistics and analysis platform for storage and registration.
In response to the attendance checking flow, the face image processing system 2 is mainly used for matching and identifying face images, and the specific flow comprises: the teaching workers collect collective photos of teaching class students through the information registration and input platform 1 of the intelligent mobile equipment end, and upload the collective photos containing face images of a plurality of students to the face image processing system 2. Thus, a single student can be prevented from queuing to collect faces, time and input cost can be saved, and the noninductive experience of the student can be improved through one-time collection. The face image processing system 2 performs operations such as receiving, preprocessing, positioning and cutting, extracting face characteristic values and the like on the collective face images, matches the collective face images to corresponding classifiers according to teaching classes selected by teaching workers, searches matched target characteristic values in the classifiers according to the extracted face characteristic values, if the obtained target characteristic values are similar, the matching of the complete face images is represented, recognition is finished, at the moment, student information corresponding to the target characteristic values is obtained, and an attendance record mark is in an attendance state. And synchronously transmitting the attendance result data to a data statistics analysis platform. And after the processes are all completed, returning the collective face image processing result to the information registration and input platform.
The data statistics and analysis platform 3 mainly stores the association relation data of the classes and the students in the teaching management, receives the matching and identifying results in the face image processing system, registers and updates the attendance conditions of the corresponding teaching classes and students according to the results, and provides the functions of visual inquiry and timing reminding for the students and teaching workers. The form of the query includes but is not limited to list, downloadable report, and the form of the reminder includes but is not limited to mail, APP (application) notification.
Fig. 7 is a block diagram of the information registration entry platform 1, and as shown in fig. 7, the information registration entry platform 1 includes: an information registration processing application unit 11, a face image acquisition unit 12, an information registration request unit 13, an information registration processing result reception unit 14, wherein:
an information registration processing application unit 11 that provides a visual form for interaction with an operator and is responsible for providing teaching class information, entry of attendance information, collection, inquiry, etc. to a learner and a teaching worker, wherein the attendance information includes, but is not limited to: class type, name, phone number, number of school, identification number, color face image (which may include a multi-learner face image).
The face image acquisition unit 12 performs photographing through a camera of the intelligent device held by an operator, performs formatting, image size and resolution inspection on the face image acquired by the camera, and converts the inspected face image into readable electronic data information. The formats of the face image include, but are not limited to, JPG (one image format), PNG (one image format), BMP (one image format).
The information registration request unit 13 is configured to package and transmit the attendance information to be processed and the face image, and the operation user query request to the face image processing system 2 and the data statistics analysis platform 3 according to a unified message format, so as to facilitate the registration, storage and face image processing of the attendance data.
The information registration processing result receiving unit 14 is responsible for notifying or visually displaying the face image processing result returned by the face image processing system 2 and the query result returned by the data statistics analysis platform 3 to the operation user in a visible message form.
Fig. 8 is a block diagram of the face image processing system 2, and as shown in fig. 8, the system 2 includes: the device comprises an information receiving and returning unit 21, a preprocessing unit 22, a positioning clipping unit 23, a face feature extraction unit 24, a classifier unit 25, a matching and identifying unit 26 and an information forwarding unit 27, wherein:
The information receiving and returning unit 21 is responsible for receiving the attendance information and the face image data information from the information registration input platform 1, splitting the message according to a unified instruction to obtain the attendance information (including the face image) and the business data to be processed, forwarding the data to other processing units for processing, and returning the final result to the information registration input platform 1.
The preprocessing unit 22 performs preprocessing operations such as noise reduction, light enhancement/attenuation, geometric correction, gray level transformation adjustment, normalization and the like on the face image based on an OpenCV (cross-platform computer vision library) image processing library algorithm according to the face image data from the information receiving and returning unit 21, so that the face image can meet the requirements of face image feature extraction. Image preprocessing algorithms include, but are not limited to: multiscale Retinex (an image enhancement algorithm) algorithm, the hopfert' S (an image processing algorithm) algorithm.
The positioning clipping unit 23 performs positioning and clipping on the face picture according to the processing result of the preprocessing unit 22, and the positioning clipping algorithm includes, but is not limited to, RGB-HIS (an image segmentation algorithm), KF (kalman filter algorithm), and SEIF (a positioning algorithm based on a filter) algorithm, which is used for judging whether a face exists or not and whether a face size and a face range exist, so that the calculation amount and the processing time can be reduced in the process of extracting the features later.
The face feature extraction unit 24 extracts face features from the processed image according to the image processing result of the positioning and clipping unit 23, and the algorithm used here includes, but is not limited to, HOUGH (HOUGH transform) and SIFT (Scale-invariant feature transform ) algorithms, and generates specific feature data. The unit can adopt a parallel processing mode when in work, mainly aims at the collective photograph containing the face head portraits of a plurality of users, can extract the face characteristics at the same time, and achieves the aim of improving the processing efficiency of the system.
The classifier unit 25 invokes the unit in response to the face image processing system 2 judging that the current operation is initial information registration entry. Generating a folder according to a unique identification code (including but not limited to a mobile phone number, a school number and an identity card ID) and a name of a single student in the background of the system, and storing face images of the student in the folder. Meanwhile, a binding relation is established among teaching classes, personnel information and face characteristic values in the system, and corresponding classifiers are generated according to a KNN model algorithm by taking the teaching classes as dimensions. When the unit works, a data association mechanism for dynamically adjusting the face feature library according to the number of students in a teaching class is adopted, namely, when the number of the students or the face images of the students change (such as class withdrawal and face image re-uploading), the classifier is trained according to the latest data, so that the efficiency of subsequent matching and recognition operation can be improved, and unnecessary overhead of a system is reduced.
The matching and recognition unit 26 is invoked in response to the face image processing system 2 determining that the face image currently operating as an attendance flow matches and recognizes. Matching the face images to the corresponding classifier according to the teaching class selected by the teaching worker, searching the target characteristic value matched with the characteristic value of the face images in the classifier, and finishing the recognition if the target characteristic value is similar to the target characteristic value, representing that the matching of the face images is finished.
And the information forwarding unit 27 acquires the student information corresponding to the target characteristic value when the face image processing system 2 judges that the face image currently operated as the attendance flow is matched and identified and the matching and identifying unit 26 processes the result to pass, records the attendance mark as an attendance state and synchronously forwards the result to the data statistics analysis platform 3 for updating processing. When the face image processing system 2 judges that the current operation is recorded as the initial information, the classifier unit 25 synchronizes the attendance information to the data statistics analysis platform 3 for registration and storage after finishing processing.
Fig. 9 is a block diagram of the data statistics analysis platform 3, and as shown in fig. 9, the data statistics analysis platform 3 includes: an information receiving and returning unit 31, a storage unit 32, a statistical analysis unit 33, wherein:
The information receiving and returning unit 31 is responsible for receiving the attendance information, the face image data processing result and the query request from the information registration input platform 1 and the face image processing system 2, splitting the message according to a unified instruction to obtain the attendance information (including the face image recognition result) and the business data, forwarding the data to other processing units for processing, and returning the final result to the information registration input platform 1 and the face image processing system 2.
The storage unit 32 is responsible for storing the association relationship data of the class and the student in the teaching management and updating the face image processing result in the face image processing system 2.
The statistical analysis unit 33 is responsible for performing statistical analysis of the data in the storage unit 32 in different dimensions, including but not limited to: the relevant program is scheduled periodically (according to day/month/quarter/year) to trigger the attendance statistics actions of the corresponding teaching class, student, and the result is returned through the information receiving and returning unit 31. The learner and the teaching staff can receive the inquiry and reminding information through the information registration processing result receiving unit 14 in the information registration input platform 1. The form of the query result comprises but is not limited to a list and a downloadable report, and the form of the reminder comprises but is not limited to mail and APP notification.
In actual operation, the units, the modules and the sub-modules may be combined or may be arranged singly, and the invention is not limited thereto.
The attendance system based on the face image provided by the embodiment of the invention realizes the functions of attendance information and face image acquisition, face image preprocessing and characteristic value extraction, attendance information and face image storage, face image matching identification, attendance information statistical analysis, attendance information processing request forwarding, attendance information processing request result returning and the like.
Based on the attendance system, when the face attendance processing is carried out on the lessons of students, three processes mainly comprise initial information registration and input, face image matching and recognition and data statistics analysis. The general generalization is: the method comprises the steps of selecting Web browsing and mobile intelligent equipment provided by an information registration and input platform 1, providing visual interaction interfaces for students and teaching workers to bind courses with the students and collect face images, then forwarding course information and the face images to a face image processing system 2, performing face image preprocessing and feature value extraction after the course information and the face image data are received by the face image processing system 2, performing feature matching and recognition, and then forwarding recognition results to a data statistics analysis platform 3. And the data statistics analysis platform 3 stores and updates the data information after receiving the data information, so as to complete the statistics analysis of the attendance data. The students or teaching workers can inquire through a visual interface provided by the information registration and input platform 1, and the data statistics analysis platform 3 informs or visually displays the inquired results to the students or teaching workers in a visual message form.
Fig. 10 is a flowchart of initial information registration entry based on the system shown in fig. 6, as shown in fig. 10, the flowchart including:
step 11: information input and face image acquisition. The teaching staff inputs relevant course information in the information registration input platform 1 in advance for the students to select, the students select courses and fill in the information (including but not limited to class types, names, mobile phone numbers, school numbers and identity card numbers) on a visual interface provided by the information registration processing application unit 11 in the information registration input platform 1, the face image acquisition unit 12 arouses cameras of intelligent equipment held by the students to take photos, and face images acquired by the cameras are subjected to formatting, image size and resolution inspection and then converted into readable electronic data information.
Step 12: course information and face image registration request. The lesson, the learner, and the face image information are packaged and transmitted to the face image processing system 2 in a unified message format by the information registration request unit 13 in the information registration entry platform 1.
Step 13: and preprocessing the face image. After the information receiving and returning unit 21 in the face image processing system 2 receives the information in step 12, the message is split according to a unified instruction to obtain attendance information (including face images) and service data, the obtained data is transmitted to the preprocessing unit 22 for face image preprocessing, and the data is transmitted to the positioning and clipping unit 23 after preprocessing is completed.
Step 14: and positioning and cutting the face image. The positioning and clipping unit 23 receives the processing result of the preprocessing unit 22, and performs positioning and clipping on the face picture, which is used for judging whether the face exists or not and the size and the range of the face, so that the calculation amount and the processing time are reduced in the process of extracting the features later. After that, the face image data after the positioning and clipping is transmitted to the face feature extraction unit 24.
Step 15: and extracting the characteristic value of the face image. And according to the processing result of the positioning and clipping unit 23, extracting the facial features of the processed image to generate specific feature data. After that, the face image processing system 2 judges that the classifier unit 25 is invoked when the current operation is registered as initial information.
Step 16: and (5) training a classifier. Generating a folder according to a unique identification code (including but not limited to a mobile phone number, a school number and an identity card ID) and a name of a single student in the background of the system, and storing face images of the student in the folder. Meanwhile, binding relations are established among courses, personnel information and face characteristic values according to the paired value data format, and corresponding classifiers are generated according to a KNN model algorithm by taking teaching classes as dimensions. In the step, a data association mechanism for dynamically adjusting the face feature library according to the number of students in a teaching class is adopted, namely, when the number of the students or the face images of the students are changed (such as class withdrawal and face image re-uploading), the classifier is trained according to the latest data, so that the efficiency of subsequent matching and recognition operation can be improved, and unnecessary overhead of a system is reduced.
Step 17: and storing course information. After the processing of the classifier unit 25 in the face image processing system 2 is finished, the course information is packed into a message according to a specific data format and is synchronized to the data statistics analysis platform 3 for registration. The information receiving and returning unit 31 located in the data statistics analysis platform 3 receives the course information and forwards it to the storage unit 32 for registration storage.
Step 18: the result is returned. After the course information is registered, the information receiving and returning unit 31 located in the data statistics analysis platform 3 returns the result to the face image processing system 2, and then the information receiving and returning unit 21 is called in the face image processing system 2 to return the result to the information registration entry platform 1. After receiving the result, the information registration processing result receiving unit 14 in the information registration entry platform 1 presents the lesson selection and face image entry results to the students in a visual form.
Fig. 11 is a flowchart of face image matching and recognition based on the system shown in fig. 6, as shown in fig. 11, the flowchart including:
step 21: and collecting collective face images. The teaching workers log in the information registration and input platform 1 by using the intelligent equipment in the class, confirm corresponding courses through the information registration and processing application unit 11, and call the cameras of the intelligent equipment to collect collective illumination through the face image collection unit 12. Thus, each student can be prevented from queuing to collect faces, the purposes of collecting faces at one time, saving time and investment cost and improving the noninductive experience of the student are achieved. And (3) carrying out formatting, image size and resolution inspection on a collective image which is acquired by a camera and contains a plurality of face images of students, and converting the collective image into readable electronic data information after inspection.
Step 22: face image matching and recognition requests. The information registration request unit 13 located in the information registration entry platform 1 packages and transmits the collective face image information to the face image processing system 2 in a specific unified message format.
Step 23: and preprocessing the face image. After receiving the information in step 22, the information receiving and returning unit 21 in the face image processing system 2 splits the message according to a unified instruction to obtain attendance information (including a face image) and service data, and transmits the data to the preprocessing unit 22 for face image preprocessing, and then transmits the preprocessed image to the positioning and clipping unit 23.
Step 24: and positioning and cutting the face image. The positioning and clipping unit 23 receives the processing result of the preprocessing unit 22, and performs positioning and clipping on the face picture, which is used for judging whether the face exists or not and the size and the range of the face, so that the calculation amount and the processing time are reduced in the process of extracting the features later. After that, the face image data after the positioning and clipping is transmitted to the face feature extraction unit 24.
Step 25: and extracting the characteristic value of the face image. And according to the processing result of the positioning and clipping unit 23, extracting the facial features of the processed facial images containing a plurality of students, and generating specific feature data according to a multitasking parallel processing mode so as to improve the image processing efficiency. Thereafter, the face image processing system 2 judges that the matching and recognition unit 26 is invoked when the face image matching and recognition is currently operated.
Step 26: and matching and identifying the face image. The matching and identifying unit 26 in the face image processing system 2 maps to the corresponding classifier according to the teaching class selected by the teaching worker, adopts a traversing circulation mechanism to search the target feature value matched with the feature value according to the feature value extracted in the collective in the classifier, and if the target feature value is similar, the matching and identifying unit represents that the matching of the face image is completed and the identification is passed.
Step 27: and registering and updating the attendance data. If the matching and identifying unit 26 processes the result, the student information corresponding to the target feature value is obtained, the attendance record is in the attendance state, and the result is synchronously forwarded to the data statistics analysis platform 3. After the information receiving and returning unit 31 in the data statistics analysis platform 3 receives the attendance result, the storage unit 32 is called to register and update the result.
Step 28: the result is returned. After the attendance data registration is updated, the information receiving and returning unit 31 in the data statistics analysis platform 3 returns the result to the face image processing system 2, and then the face image processing system 2 calls the information receiving and returning unit 21 to return the result to the information registration entry platform 1. After receiving the result, the information registration processing result receiving unit 14 in the information registration entry platform 1 presents the face image matching and recognition result to the teaching staff in a visual form.
Fig. 12 is a flow chart of statistical analysis of attendance data based on the system of fig. 6, as shown in fig. 12, the flow comprising:
step 31: data statistics analysis triggers. The statistical analysis action may be triggered in 2 ways as follows: firstly, a student actively triggers a query request through an information registration processing application unit 11 positioned in an information registration input platform 1; and secondly, a statistical analysis unit 33 in the data statistical analysis platform 3 periodically dispatches related program triggers according to the data in the storage unit 32. Wherein the periodic includes but is not limited to: at the end of the course, and according to/day/month/quarter/year, the statistical analysis content includes, but is not limited to, corresponding teaching class, student attendance, attendance ranking statistics.
Step 32: and returning the statistical result. The information receiving and returning unit 31 in the data statistics analysis platform 3 returns the data result of active inquiry or periodical statistics to the information registration entry platform 1, and the information registration processing result receiving unit 14 positioned on the information registration entry platform 1 receives the inquiry statistics result and displays the inquiry statistics result to students or teaching workers on the information registration entry platform 1 in a visual form of a list and a downloadable report through a notification reminding form.
As can be seen from the above description, the embodiment of the present invention provides an attendance system based on face images, wherein the information registration and input platform is used for providing teaching information (including but not limited to courses, classes, etc.) for students and teaching workers, collecting and inputting face image information, and transmitting collected face image data to the face image processing system. The face image processing system receives teaching information and face images, performs image preprocessing, image feature extraction, image matching and recognition, and generates image recognition results. And the face image processing system sends the identification result to the data statistics analysis platform to carry out statistics, analysis and follow-up notification actions of the data. The face image and teaching information data are transmitted in the corresponding network through TSL (Transport Layer Security, secure transmission layer protocol) protocol in the circulation process of the information registration and input platform, the face image processing system and the data statistics and analysis platform, decryption and verification are carried out when the data reach the distribution system, and TSL communication is established with the next processing system to transmit data information after the processing is completed, so that confidentiality and integrity of information flow in the transmission process are guaranteed.
Fig. 13 is a schematic diagram of an electronic device according to an embodiment of the invention. The electronic device shown in fig. 13 is a general-purpose data processing apparatus including a general-purpose computer hardware structure including at least a processor 1301 and a memory 1302. The processor 1301 and the memory 1302 are connected by a bus 1303. The memory 1302 is adapted to store one or more instructions or programs executable by the processor 1301. The one or more instructions or programs are executed by the processor 1301 to implement the steps in the image recognition based attendance method described above.
The processor 1301 may be a separate microprocessor or a collection of one or more microprocessors. Thus, the processor 1301 performs the method flow of the embodiment of the present invention described above to realize processing of data and control of other devices by executing the commands stored in the memory 1302. The bus 1303 connects the above components together, and connects the above components to the display controller 1304 and the display device, and to an input/output (I/O) device 1305. Input/output (I/O) device 1305 may be a mouse, keyboard, modem, network interface, touch input device, somatosensory input device, printer, and other devices known in the art. Typically, an input/output (I/O) device 1305 is coupled to the system through an input/output (I/O) controller 1306.
The memory 1302 may store software components such as an operating system, communication modules, interaction modules, and application programs, among others. Each of the modules and applications described above corresponds to a set of executable program instructions that perform one or more functions and methods described in the embodiments of the invention.
The embodiment of the invention also provides a computer readable storage medium, on which a computer program is stored, which when being executed by a processor, is used for realizing the steps of the attendance checking method based on image recognition.
In summary, the embodiment of the invention provides an attendance scheme based on face image recognition, which collects collective face images by means of convenience of mobile intelligent equipment, and completes attendance by matching and recognizing face image characteristics. The embodiment of the invention replaces the traditional inductive operation flow by the technical means, improves the attendance checking efficiency, can conveniently match with the student information according to the face picture information, can rapidly carry out attendance checking statistics and analysis work, ensures the high efficiency of attendance checking management, and provides a more intelligent, more accurate and more efficient management means for attendance checking management.
Preferred embodiments of the present invention are described above with reference to the accompanying drawings. The many features and advantages of the embodiments are apparent from the detailed specification, and thus, it is intended by the appended claims to cover all such features and advantages of the embodiments which fall within the true spirit and scope thereof. Further, since numerous modifications and changes will readily occur to those skilled in the art, it is not desired to limit the embodiments of the invention to the exact construction and operation illustrated and described, and accordingly, all suitable modifications and equivalents may be resorted to, falling within the scope thereof.
It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The principles and embodiments of the present invention have been described in detail with reference to specific examples, which are provided to facilitate understanding of the method and core ideas of the present invention; meanwhile, as those skilled in the art will have variations in the specific embodiments and application scope in accordance with the ideas of the present invention, the present description should not be construed as limiting the present invention in view of the above.
Claims (12)
1. An attendance checking method based on image recognition, which is characterized by comprising the following steps:
obtaining attendance data to be processed, wherein the attendance data comprises: a collective image containing a plurality of user face images and corresponding activity information;
preprocessing the collective image and identifying a face image in the collective image;
performing matching operation according to the activity information and the identified face image and pre-stored activity registration information, wherein the activity registration information comprises: user information and face images of users needing to participate in activities;
identifying whether the user needing to participate in the activity participates in the activity or not according to the matching operation result so as to generate attendance result data;
the matching operation according to the activity information and the identified face image and the pre-stored activity registration information comprises the following steps:
determining activity registration information of a corresponding category according to the activity information;
matching the recognized face image based on a traversal circulation mechanism according to the determined activity registration information of the corresponding category;
generating activity registration information according to the courses as categories, and establishing corresponding relations among the courses, the trainees and face images thereof;
the face image and the corresponding active information are transmitted in the corresponding network through the secure transmission layer protocol in the circulation process, decryption and verification are carried out when the data reach the distribution system, and the secure transmission layer protocol communication is established with the next processing system to transmit the data information after the processing is completed.
2. The method of claim 1, wherein when a user is required to engage in a plurality of different activities, the method further comprises:
classifying the activity registration information based on the trained classification model;
and generating the activity registration information taking the activity information as a category according to the classification processing result.
3. The method of claim 1, wherein preprocessing the collective image and identifying face images therein comprises:
preprocessing the collective image;
and carrying out face feature extraction operation on the preprocessed collective images based on the parallel processing mode so as to identify the face images in the collective images.
4. The method according to claim 1, wherein the method further comprises:
and counting attendance result data according to the preset rules by using the activity information or the user information.
5. The method of claim 1, wherein obtaining attendance data to be processed comprises:
a collective image of users participating in an activity is acquired by an image pickup apparatus.
6. An attendance device based on image recognition, characterized in that the device comprises:
the data acquisition unit is used for acquiring the attendance data to be processed, and the attendance data comprises: a collective image containing a plurality of user face images and corresponding activity information;
The image recognition unit is used for preprocessing the collective image and recognizing a face image in the collective image;
a matching unit, configured to perform a matching operation according to the activity information and the identified face image, and pre-stored activity registration information, where the activity registration information includes: user information and face images of users needing to participate in activities;
the identification unit is used for identifying whether the user needing to participate in the activity participates in the activity according to the matching operation result so as to generate attendance result data;
the matching unit includes:
the activity registration information determining module is used for determining activity registration information of a corresponding category according to the activity information;
the matching module is used for carrying out matching operation on the recognized face images based on a traversal circulation mechanism according to the determined activity registration information of the corresponding category;
generating activity registration information according to the courses as categories, and establishing corresponding relations among the courses, the trainees and face images thereof;
the face image and the corresponding active information are transmitted in the corresponding network through the secure transmission layer protocol in the circulation process, decryption and verification are carried out when the data reach the distribution system, and the secure transmission layer protocol communication is established with the next processing system to transmit the data information after the processing is completed.
7. The apparatus of claim 6, wherein when a user is required to engage in a plurality of different activities, the apparatus further comprises:
the classification unit is used for classifying the activity registration information based on the trained classification model;
and the activity registration information generating unit is used for generating activity registration information taking the activity information as a category according to the classification processing result.
8. The apparatus according to claim 6, wherein the image recognition unit includes:
the preprocessing module is used for preprocessing the collective image;
and the image recognition module is used for carrying out face feature extraction operation on the preprocessed collective images based on the parallel processing mode so as to recognize the face images in the collective images.
9. The apparatus of claim 6, wherein the apparatus further comprises:
and the statistics unit is used for counting the attendance result data according to the activity information or the user information according to the preset rule.
10. The apparatus according to claim 6, wherein the data acquisition unit is specifically configured to:
a collective image of users participating in an activity is acquired by an image pickup apparatus.
11. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the steps of the image recognition based attendance method of any one of claims 1 to 5 when the program is executed.
12. A computer-readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the image recognition-based attendance method as claimed in any one of claims 1 to 5.
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Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106204780A (en) * | 2016-07-04 | 2016-12-07 | 武汉理工大学 | A kind of based on degree of depth study and the human face identification work-attendance checking system and method for cloud service |
| CN107481343A (en) * | 2017-07-22 | 2017-12-15 | 华中师范大学 | A kind of check class attendance based on face recognition technology is registered system and its method of work |
| CN108022318A (en) * | 2017-12-28 | 2018-05-11 | 上海享服信息技术有限公司 | More people's recognition of face attendance checking systems and its Work attendance method |
| CN108875606A (en) * | 2018-06-01 | 2018-11-23 | 重庆大学 | A kind of classroom teaching appraisal method and system based on Expression Recognition |
-
2020
- 2020-02-26 CN CN202010118627.2A patent/CN111339939B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106204780A (en) * | 2016-07-04 | 2016-12-07 | 武汉理工大学 | A kind of based on degree of depth study and the human face identification work-attendance checking system and method for cloud service |
| CN107481343A (en) * | 2017-07-22 | 2017-12-15 | 华中师范大学 | A kind of check class attendance based on face recognition technology is registered system and its method of work |
| CN108022318A (en) * | 2017-12-28 | 2018-05-11 | 上海享服信息技术有限公司 | More people's recognition of face attendance checking systems and its Work attendance method |
| CN108875606A (en) * | 2018-06-01 | 2018-11-23 | 重庆大学 | A kind of classroom teaching appraisal method and system based on Expression Recognition |
Non-Patent Citations (1)
| Title |
|---|
| 方冠男.基于视频流人脸识别的课堂考勤系统的设计与实现.中国优秀硕士学位论文全文数据库信息科技辑.2018,(第12期),17-29页. * |
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