Book label identification method and system based on dot matrix technology and AI analysis

Abstract

The invention relates to a book label identification method and system based on a dot matrix technology and AI analysis, and the method comprises the steps: carrying out the hierarchical coding of an identity region, a chapter region and an exercise region of a book based on a preset coding rule; when the code information sent by the identification terminal is received, identifying the code information to confirm the identity information of the student to which the book belongs; after identification of the identity information is completed, acquiring correction information of the current chapter exercise area; and when the correction completion information of the current chapter is recognized, the obtained correction information, the identity information and the chapter information are stored in an associated manner. The method has the advantages that a teacher can conveniently correct the book exercise book, and the correction efficiency is improved.

Description

Technical Field

[0001] This application relates to the technical field of dot matrix recognition, and in particular to a method and system for recognizing book tags based on dot matrix technology and AI analysis. Background Technology

[0002] Currently, in daily teaching activities, in order to better statistically analyze and demonstrate students' mastery of knowledge, dot matrix technology is used to correct students' answers. Teachers correct the paper answers and use dot matrix recognition technology to upload the students' answers and the teachers' corrections to the server and terminal for statistical display, making it more efficient and convenient to statistically analyze students' answers.

[0003] However, in the existing application scenarios, teachers need to correct the same workbook or book for students multiple times, and the chapters, exercise types and locations are different each time. The previous method of single paper correction statistics is not applicable. Teachers need to enter chapter information each time they correct, which makes the efficiency of teachers correcting book-type workbooks low. Therefore, it needs to be improved. Summary of the Invention

[0004] Based on dot matrix technology, in order to facilitate teachers' grading of book-type workbooks and improve grading efficiency, this application provides a book tag recognition method and system based on dot matrix technology and AI analysis.

[0005] The above-mentioned objective of this application is achieved through the following technical solution:

[0006] A book tag recognition method based on dot matrix technology and AI analysis includes the following steps:

[0007] Based on preset coding rules, the identity area, chapter area, and exercise area of ​​the book are coded in layers.

[0008] When the coded information sent by the identification terminal is received, the coded information is identified to confirm the identity information of the student to whom the book belongs;

[0009] After the identity information is identified, the grading information for the current chapter's exercises area is retrieved;

[0010] When the completion of the current chapter's corrections is detected, the obtained correction information is associated with and stored along with the identity information and chapter information.

[0011] By adopting the above technical solution, students' workbooks are encoded in different dimensions. Each area—the identity area for identifying the student, the chapter area for determining the chapter being graded, and the exercise area for identifying exercises and grading information—has a unique code. When a teacher grades exercises for a particular chapter in a student's workbook, the identification terminal acquires the code and grading information. Simultaneously, the workbook's current information, chapter information, and the graded content are all associated, bound, and stored. Therefore, during multiple grading sessions, the teacher accurately and efficiently associates the graded content with the corresponding chapter and student identity, facilitating the grading of book-based workbooks and improving grading efficiency.

[0012] Optionally, the identity area is set on the surface of the book, and the step of performing layered encoding processing on the identity area, chapter area, and exercise area of ​​the book based on preset encoding rules includes:

[0013] Based on the identity information of different students, coordinate regions corresponding to different identity information are pre-selected in a pre-constructed coordinate system;

[0014] Within a selected single coordinate region, the coordinate region is divided into multiple coordinate sub-regions based on different chapter information;

[0015] Within the selected coordinate sub-region, a portion of the coordinate range is subjected to dense coding processing, and the densely coded coordinate range is used as the exercise area.

[0016] By adopting the above technical solution, the identity area is set on the surface of the student's books and workbooks, which facilitates the identification of the student each time the workbook is graded. By constructing a coordinate system and assigning a unique coordinate path to each identity information, chapter information, and exercise area, the identity, chapter, and content of the grading object are identified synchronously. Dense coding processing is performed in the exercise area to make the capture of changes in the coordinate sequence more precise, thereby making the reproduction of the grading information and the student's answer information more accurate.

[0017] Optionally, the step of identifying the encoded information to confirm the book's identity information upon receiving the encoded information from the identification terminal includes:

[0018] When the coded information sent by the recognition terminal is received, the coordinate data sequence representing the handwriting and the corresponding timestamp information in the coded information are obtained.

[0019] Based on the coordinate data sequence and the corresponding timestamp information, determine whether to trigger an identity verification command;

[0020] If so, then filter the identity information that matches the current coordinate data sequence from the preset student identity database.

[0021] By adopting the above technical solution, the handwriting of the user on the identification terminal can be obtained through the coordinate data sequence and the corresponding timestamp information. The handwriting is in the time dimension. In order to avoid accidentally triggering the identity information recognition program when the workbook is not corrected, a judgment step is set to judge the handwriting of the identification terminal in the identity area to verify whether the identity recognition program is triggered. When the identity confirmation command is triggered, the student's identity information of the currently matched book and workbook is used, which facilitates the subsequent binding of correction information and chapter information.

[0022] Optionally, the step of obtaining the grading information for the current chapter's exercises area after completing the identification of identity information includes:

[0023] When the correction information is received from the recognition terminal, the coordinate data sequence of the correction information and the corresponding timestamp information are recognized.

[0024] Determine the coordinate sub-region to which the coordinate data sequence belongs and match the corresponding chapter information;

[0025] The received coordinate data sequence and timestamp information are converted into handwriting information in the coordinate system in real time, and the handwriting information is pre-associated with the chapter information;

[0026] When a change in the coordinate sub-region to which the coordinate data sequence belongs is detected, the handwriting information is associated with the changed new chapter information.

[0027] By adopting the above technical solution, the coordinate sub-region to which a workbook belongs can be identified through the coordinate data sequence in the correction information, and the chapter information currently being corrected can be quickly matched. At the same time, the corresponding handwriting information is generated in real time and bound to the chapter information. When the teacher changes the chapter of the workbook for correction, the coordinate sub-region to which the corresponding identified coordinate data sequence belongs changes. Then, the corresponding handwriting information is associated with the chapter information of the changed coordinate sub-region, so as to achieve the effect of real-time and accurate association of correction information.

[0028] Optionally, after the step of obtaining the grading information of the current chapter's exercise area after completing the identification of identity information, the method further includes:

[0029] Determine whether the currently received handwriting information triggers an erasure or deletion command;

[0030] If so, the target handwriting information to be deleted is determined based on the alteration recognition rules;

[0031] Remove the association between the target handwriting information and the chapter information, and delete the target handwriting information along with the currently triggered handwriting information.

[0032] By adopting the above technical solution, in order to make the final electronic version of the correction content more concise, the terminal can identify the erased handwriting triggered by the physical workbook and delete the identified handwriting in the corrected parts, and then re-correct the corrections. This makes the correction information presented on the terminal more concise and the display effect better.

[0033] Optionally, the step of determining whether the currently received handwriting information triggers an erasure or deletion command includes the following steps:

[0034] Obtain the coordinate data sequence and timestamp information of the handwriting information, and send the coordinate data sequence and the corresponding timestamp information to the preset alteration handwriting recognition model;

[0035] When the alteration handwriting recognition model receives a coordinate data sequence, it obtains handwriting information within a preset time period based on the timestamp information of the current coordinate data sequence.

[0036] Determine whether the current coordinate data sequence overlaps with the coordinate data sequence within a preset time period, and obtain overlap information;

[0037] The alteration handwriting recognition model is based on a pre-set alteration handwriting database. It identifies whether the current coordinate data sequence is an alteration handwriting and obtains the degree of matching of the alteration handwriting.

[0038] Based on the overlap information and the degree of matching of the correction handwriting, it is determined whether the correction / deletion command should be triggered.

[0039] By adopting the above technical solution, in order to more accurately determine whether a teacher has triggered an erasure or deletion command through the recognition terminal, the coordinate data sequence and timestamp information in the handwriting information are obtained and sent to a pre-trained erasure handwriting recognition model. The erasure handwriting recognition model only allows the repair of handwriting information generated within a preset time period to avoid excessive storage of handwriting information in the system. Furthermore, since teachers' habit of erasing original handwriting is to make changes on top of the original handwriting information, the coordinate data is obtained by comparing the overlap of each unique coordinate point in the coordinate data sequence. The model uses overlapping information to determine whether there is overlapping handwriting and the size of the overlapping area. Additionally, it pre-stores a database of altered handwriting samples, containing coordinate sequence features of various altered handwriting samples. This allows the model to determine whether the currently overlapping handwriting is an alteration. For example, a teacher's intention to correct an error might simply be to modify the existing handwriting, not to delete it. Therefore, by identifying altered handwriting samples covering the overlapping information, the model can more accurately determine whether the original handwriting needs to be deleted, making the teacher's intention to modify the handwriting more precise.

[0040] Optionally, the step of determining the target handwriting information to be deleted based on the alteration recognition rules includes:

[0041] The correction handwriting recognition model is based on overlap information to obtain coordinate points that overlap with the current coordinate data sequence;

[0042] Based on timestamp information, determine the coordinate data sequence to which the overlapping coordinate points belong;

[0043] The coordinate data sequence with more than a threshold number of overlapping coordinate points is used as the target handwriting information to be deleted.

[0044] By adopting the above technical solution, since not all coordinate points in the overlapping coordinate data sequence are completely overlapping, in order to more accurately determine the target handwriting to be deleted by the recognition terminal, the overlapping coordinate points in the coordinate data sequence are first found. Based on the timestamp information, the coordinate data sequence of the coordinate point can be determined, that is, the handwriting to which the current coordinate point belongs can be determined. For example, which character the overlapping coordinate point is. If the number of overlapping coordinate points on the character exceeds a threshold, the handwriting information is considered to be the target handwriting information to be deleted. That is, if the area covered by the scribbled handwriting of a certain character exceeds a certain threshold, it is considered that the recognition terminal wants to delete the character. This is applicable to situations where teachers give the wrong score, write the wrong correct or wrong symbol, or write the wrong prompt when grading homework through the recognition terminal.

[0045] The second objective of this invention is achieved through the following technical solution:

[0046] A book tag recognition system based on dot matrix technology and AI analysis includes:

[0047] The encoding processing module is used to perform layered encoding processing on the identity area, chapter area, and exercise area of ​​the book based on preset encoding rules;

[0048] The identity recognition module is used to identify the coded information sent by the recognition terminal to confirm the identity information of the student to whom the book belongs.

[0049] The grading recognition module is used to obtain the grading information of the current chapter's exercise area after the identity information has been recognized;

[0050] The association module is used to associate and store the obtained correction information with the identity information and chapter information when the correction completion information of the current chapter is detected.

[0051] The above-mentioned objective three of this application is achieved through the following technical solution:

[0052] A computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the above-described book tag recognition method based on dot matrix technology and AI analysis.

[0053] The fourth objective of this application is achieved through the following technical solution:

[0054] A computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the above-described book tag recognition method based on dot matrix technology and AI analysis.

[0055] In summary, this application includes at least one of the following beneficial technical effects:

[0056] 1. By encoding students' workbooks in different dimensions, each area—including the student identification area, the chapter area for determining the chapter being graded, and the exercise area for identifying exercises and grading information—has a unique code. When a teacher grades exercises for a particular chapter in a student's workbook, the identification terminal acquires the encoding and grading information. Simultaneously, the workbook's current information, chapter information, and the graded content are all associated, bound, and stored. This ensures that during multiple grading sessions, the graded content is accurately and efficiently associated with the corresponding chapter and student identity, facilitating grading of book-based workbooks and improving grading efficiency.

[0057] 2. By constructing a coordinate system and assigning a unique coordinate path to each identity information, chapter information, and exercise area, the synchronous recognition of the grading identity, chapter, and content is achieved. Dense coding processing is performed in the exercise area to make the capture of coordinate sequence changes more precise, thereby making the reproduction of grading information and student answer information more accurate.

[0058] 3. The coordinate sub-region to which a workbook belongs can be identified by the coordinate data sequence in the grading information, and the chapter information currently being graded can be quickly matched. At the same time, the corresponding handwriting information is generated in real time and bound to the chapter information. When the teacher changes the chapter of the workbook for grading, the coordinate sub-region to which the corresponding coordinate data sequence belongs changes. Then, the corresponding handwriting information is associated with the chapter information of the changed coordinate sub-region, so as to achieve the effect of real-time and accurate association of grading information.

[0059] 4. The correction handwriting recognition model also pre-stores a correction handwriting database to store the coordinate sequence features of various correction handwritings. This database is used to determine whether the currently covered handwriting is a correction handwriting. For example, a teacher's intention to correct is only to make corrections on the original handwriting, not to delete the original handwriting information because of their own correction error. Therefore, by recognizing the correction handwriting information covered by the correction handwriting, it is possible to more accurately determine whether the original handwriting has been deleted, making the teacher's intention to make corrections more accurate. Attached Figure Description

[0060] Figure 1 This is a flowchart illustrating an embodiment of a book tag recognition method based on dot matrix technology and AI analysis according to this application.

[0061] Figure 2 This is a flowchart of step S30 in an embodiment of a book tag recognition method based on dot matrix technology and AI analysis according to this application;

[0062] Figure 3 This is a flowchart of step S31 in an embodiment of a book tag recognition method based on dot matrix technology and AI analysis according to this application; Figure 4 This is a schematic block diagram of a computer device according to this application. Detailed Implementation

[0063] The following is in conjunction with the appendix Figure 1-4 This application will be described in further detail.

[0064] In the following embodiments, such as Figure 1 As shown, this application discloses a book tag recognition method based on dot matrix technology and AI analysis, which specifically includes the following steps:

[0065] S10: Based on preset encoding rules, perform layered encoding processing on the identity area, chapter area, and exercise area of ​​the book;

[0066] In this embodiment, the encoding rule refers to editing the student's books and workbooks with different code point coordinates and densities. This includes different coordinates for code points representing different identity areas, chapter areas, and exercise areas, and different code point densities among these areas to distinguish between different identities, chapters, and exercise areas. The identity area identifies the student to whom the workbook belongs. It is placed on the surface of the book and uses a code point paper attachment method to facilitate teacher identification of student identity information during grading. The chapter information confirms the chapter the teacher is currently grading. The exercise area represents the location where the teacher writes their corrections and is used to capture handwriting.

[0067] Specifically, step S10 includes the following steps:

[0068] S11: Based on the identity information of different students, pre-select the coordinate regions corresponding to different identity information in the pre-constructed coordinate system;

[0069] S12: Within a selected single coordinate region, divide the coordinate region into multiple coordinate sub-regions based on different chapter information;

[0070] S13: Within the selected coordinate sub-region, select a portion of the coordinate range for dense coding processing, and use the densely coded coordinate range as the exercise area.

[0071] In this approach, by constructing a sufficiently large coordinate system, different coordinate regions are selected for different students. The characteristics of all coordinate points in the region can represent the student's identity. In other embodiments, different code point shapes, types, or grayscale values ​​can also be used to represent code points for different student identity information.

[0072] After selecting the coordinate region, multiple coordinate sub-regions are further divided based on a unique coordinate path. The coordinate points in each coordinate sub-region have the characteristic of representing the same chapter. After selecting the coordinate sub-region, a portion of the coordinate range within the coordinate sub-region is selected for dense coding. When teachers use a dot matrix pen to correct and write on this densely coded coordinate range, they can recognize that the current area is an exercise area. Since the coordinate range is contained within the coordinate sub-region, it is also possible to identify the coordinate sub-region to which the coordinate range belongs and automatically match the chapter information corresponding to the current correction page.

[0073] S20: Upon receiving the encoded information from the identification terminal, identify the encoded information to confirm the identity information of the student to whom the book belongs;

[0074] In this embodiment, the identification terminal is a dot matrix pen used by teachers or students. The encoded information includes the connection sequence, pressure, and time of the code dots on the book or exercise book, namely the coordinate data sequence, handwriting pressure, and corresponding timestamp information. By writing on the dotted paper on the surface of the book or exercise book, the identity information of the student to whom the book or exercise book to be graded is first confirmed.

[0075] Specifically, step S20 includes the following steps:

[0076] S21: When receiving the encoded information sent by the recognition terminal, obtain the coordinate data sequence representing the handwriting and the corresponding timestamp information in the encoded information;

[0077] S22: Based on the coordinate data sequence and the corresponding timestamp information, determine whether to trigger the identity verification command;

[0078] S23: If so, then filter the identity information that matches the current coordinate data sequence from the preset student identity database.

[0079] To prevent accidental triggering of the identity verification process when workbooks are not being graded, the handwriting used for identity verification must be written in a preset order to trigger the process. For example, for checkmarks, a PVC protective sleeve can be placed on the outside of the marking paper to allow for multiple writings without damaging the marking paper. A vibration alert can be set on the recognition terminal to prompt teachers to accurately trigger the identity verification command. If the identity verification command is not triggered, the subsequent grading and synchronous display process will not be started to avoid accidental triggering of the grading process. The student identity database stores student identity information hierarchically across different grades and classes within the school.

[0080] S30: After the identity information is identified, obtain the grading information for the current chapter's exercises area;

[0081] In this embodiment, the grading information refers to the handwriting of the terminal's dot matrix pen in the exercise area, including coordinate data sequence, pen pressure, and timestamp information. Teachers can identify the current chapter's exercise area whether they are writing in the exercise area or not, but only the writing in the exercise area will be synchronized to the subsequent display terminal as grading information.

[0082] Specifically, refer to Figure 2 Step S30 includes the following steps:

[0083] S301: When receiving the correction information sent by the identification terminal, identify the coordinate data sequence of the correction information and the corresponding timestamp information;

[0084] S302: Determine the coordinate sub-region to which the coordinate data sequence belongs and match the corresponding chapter information;

[0085] S303: Convert the received coordinate data sequence and timestamp information into handwriting information in the coordinate system in real time, and associate the handwriting information with the chapter information in advance;

[0086] S304: When a change in the coordinate sub-region to which the coordinate data sequence belongs is detected, the handwriting information is associated with the changed new chapter information.

[0087] Specifically, the coordinate sub-region to which the current correction information belongs is determined by the coordinate point features in the coordinate data sequence, such as the first and last values, shape, and color of the coordinate points. The corresponding chapter information is then matched and the chapter information is associated. The handwriting in the correction information is then obtained and associated with the chapter information. The handwriting information is then displayed on the display terminal or stored and archived in real time. When the coordinate data sequence of the second-level recognition terminal in the exercise area changes, the features of the coordinates in the coordinate data sequence change. In this case, step S32 is automatically started to identify the coordinate sub-region and determine the new chapter information. The handwriting information is then associated with the new chapter information.

[0088] After step S30, the following steps are also performed:

[0089] S31: Determine whether the currently received handwriting information triggers an erasure or deletion command;

[0090] S32: If so, determine the target handwriting information to be deleted based on the erasure recognition rules;

[0091] S33: Remove the association between the target handwriting information and the chapter information, and delete the target handwriting information and the currently triggered handwriting information together.

[0092] In this embodiment, during the daily homework grading process, teachers may modify the grading marks or correct the handwriting of students' answers. In order to make the subsequent storage or display of the grading information more concise, it is determined whether the original handwriting information covered by the correction needs to be deleted under different circumstances. The original incorrect handwriting and the correction handwriting are deleted together, making the obtained handwriting information more concise.

[0093] Among them, reference Figure 3 The specific triggering steps for the alteration / deletion command in step S31 include:

[0094] S311: Obtain the coordinate data sequence and timestamp information of the handwriting information, and send the coordinate data sequence and the corresponding timestamp information to the preset alteration handwriting recognition model;

[0095] S312: When the alteration handwriting recognition model receives a coordinate data sequence, it obtains handwriting information within a preset time period based on the timestamp information of the current coordinate data sequence.

[0096] S313: Determine whether the current coordinate data sequence overlaps with the coordinate data sequence within a preset time period, and obtain overlap information;

[0097] S314: The alteration handwriting recognition model is based on a preset alteration handwriting database to identify whether the current coordinate data sequence is an alteration handwriting and to obtain the degree of matching of the alteration handwriting.

[0098] S315: Based on the overlap information and the degree of matching of the correction handwriting, determine whether the correction / deletion command is triggered.

[0099] In this embodiment, the alteration handwriting model is a neural network-trained model used to identify repeated coordinate points and determine whether the handwriting is altered based on the similarity of coordinate sequences. The preset time period is usually set to one day. Overlap information refers to whether the coordinate points of newly acquired handwriting information overlap with the coordinate data sequence within the preset time period, the degree of overlap of a single coordinate data sequence, and the number of overlapping coordinate data sequences.

[0100] The alteration handwriting database serves as the training set for the alteration handwriting recognition model. By training on the altered handwriting and storing its features in the database, the model can determine the degree of matching between the altered handwriting and the features in the altered handwriting database. If the degree of matching between the altered handwriting and the features in the altered handwriting database reaches a preset degree of matching, then the current handwriting information is determined to be an altered handwriting.

[0101] When the number of overlapping coordinate points in the coordinate data sequence exceeds a threshold, and the current handwriting information matches the characteristics of altered handwriting, an alteration deletion command is triggered. When a teacher corrects a student's handwriting using a recognition terminal, for example, changing 17 to 19, with the 9 covering the 7, the coordinate data sequence shows overlap. However, based on the degree of matching of the current altered handwriting, it is not considered an alteration; that is, the teacher's modification traces are preserved. This avoids the accidental deletion of original handwriting.

[0102] Step S32 includes the following steps:

[0103] S321: The alteration handwriting recognition model is based on overlap information to obtain coordinate points that overlap with the current coordinate data sequence;

[0104] S322: Based on timestamp information, determine the coordinate data sequence to which the overlapping coordinate points belong;

[0105] S323: Use the coordinate data sequence with the number of overlapping coordinate points exceeding the threshold as the target handwriting information to be deleted.

[0106] In this embodiment, overlapping coordinate points are first obtained. These overlapping coordinate points include one or more complete coordinate data sequences that overlap, i.e., they overlap with one or more character handwritings. Therefore, it is necessary to determine the handwriting information to be deleted. The time stamp information can be used to determine that there is a long time interval between adjacent payment writings, so the handwriting information to which the overlapping coordinate points belong can be distinguished.

[0107] S40: When the correction completion information of the current chapter is detected, the obtained correction information is associated with the identity information and chapter information and stored.

[0108] In this embodiment, if the chapter information of the grading information changes or exceeds a certain preset time, it is considered that the grading completion information has been issued to the current chapter, and the grading information, identity information and chapter information of the current chapter are temporarily stored together.

[0109] In other embodiments, the teacher identifies whether the book assignment has been graded by recognizing that the terminal writes in the submission sub-area of ​​the exercise area to generate a submission signal. Since the teacher may repeatedly modify the exercise area of ​​the same chapter during the grading process, for example, when grading chapter B, the teacher finds that the grading of chapter A just now needs to be corrected, in order to ensure the accuracy of the associated storage of identity grading information, identity information and chapter information, the chapter grading completion information is only considered to have been issued after the submission signal is generated.

[0110] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0111] In one embodiment, a book label recognition system based on dot matrix technology and AI analysis is provided. This book label recognition system based on dot matrix technology and AI analysis corresponds one-to-one with the book label recognition method based on dot matrix technology and AI analysis described in the above embodiments. The book label recognition system based on dot matrix technology and AI analysis includes:

[0112] The encoding processing module is used to perform layered encoding processing on the identity area, chapter area, and exercise area of ​​the book based on preset encoding rules;

[0113] The identity recognition module is used to identify the coded information sent by the recognition terminal to confirm the identity information of the student to whom the book belongs.

[0114] The grading recognition module is used to obtain the grading information of the current chapter's exercise area after the identity information has been recognized;

[0115] The association module is used to associate and store the obtained correction information with the identity information and chapter information when the correction completion information of the current chapter is detected.

[0116] Optionally, the encoding processing module includes:

[0117] The identity coding submodule is used to pre-select the coordinate regions corresponding to different identity information in a pre-constructed coordinate system based on the identity information of different students.

[0118] The chapter coding submodule is used to divide a selected single coordinate region into multiple coordinate sub-regions based on different chapter information.

[0119] The Dense Coding submodule is used to perform dense coding on a selected range of coordinates within a selected coordinate subregion, and then use the densely coded range as the exercise area.

[0120] Optionally, the identity recognition module includes:

[0121] The encoding acquisition submodule is used to acquire the coordinate data sequence representing the handwriting and the corresponding timestamp information in the encoding information when the encoding information is received from the recognition terminal.

[0122] The trigger recognition submodule is used to determine whether to trigger an identity verification command based on the coordinate data sequence and the corresponding timestamp information.

[0123] The identity matching submodule is used to filter identity information that matches the current coordinate data sequence from the preset student identity database if the condition is met.

[0124] Optionally, the correction recognition module includes:

[0125] The correction recognition submodule is used to recognize the coordinate data sequence and corresponding timestamp information of the correction information when it receives correction information from the recognition terminal.

[0126] The chapter matching submodule is used to determine the coordinate sub-region to which the coordinate data sequence belongs and to match the corresponding chapter information;

[0127] The handwriting association submodule is used to convert the received coordinate data sequence and timestamp information into handwriting information in the coordinate system in real time, and to associate the handwriting information with the chapter information in advance.

[0128] When a change in the coordinate sub-region to which the coordinate data sequence belongs is detected, the handwriting information is associated with the changed new chapter information.

[0129] Optional, also includes:

[0130] The erasure detection module is used to determine whether the currently received handwriting information triggers an erasure or deletion command;

[0131] The tampering target module is used to determine the target handwriting information to be deleted based on the tampering recognition rules if the handwriting is altered.

[0132] The erasure and deletion module is used to remove the association between the target handwriting information and the chapter information, and delete the target handwriting information and the handwriting information that triggered the erasure together.

[0133] Optionally, the alteration detection module includes:

[0134] The data sending submodule is used to acquire the coordinate data sequence and timestamp information of handwriting information, and send the coordinate data sequence and the corresponding timestamp information to the preset tamper handwriting recognition model;

[0135] The handwriting acquisition submodule is used to obtain handwriting information within a preset time period based on the timestamp information of the current coordinate data sequence when the tamper handwriting recognition model receives the coordinate data sequence.

[0136] The overlap detection submodule is used to determine whether the current coordinate data sequence overlaps with the coordinate data sequence within a preset time period and to obtain overlap information.

[0137] The alteration matching degree submodule is used by the alteration handwriting recognition model to identify whether the current coordinate data sequence is an alteration handwriting based on a preset alteration handwriting database, and to obtain the degree of matching of the alteration handwriting.

[0138] The trigger judgment submodule is used to determine whether to trigger the erasure / deletion command based on the overlap information and the degree of matching of the erasure handwriting.

[0139] Optional, the target module for modification includes:

[0140] The overlapping coordinate point submodule is used by the tamper handwriting recognition model to obtain coordinate points that overlap with the current coordinate data sequence based on the overlap information.

[0141] The coordinate point attribution determination submodule is used to determine the coordinate data sequence to which overlapping coordinate points belong based on timestamp information;

[0142] The coordinate point judgment submodule is used to identify coordinate data sequences with more than a threshold number of overlapping coordinate points as target handwriting information to be deleted.

[0143] Specific limitations regarding the book label recognition system based on dot matrix technology and AI analysis can be found in the limitations of the book label recognition method based on dot matrix technology and AI analysis mentioned above, and will not be repeated here. Each module in the aforementioned book label recognition system based on dot matrix technology and AI analysis can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the memory of a computer device as software, so that the processor can call and execute the corresponding operations of each module.

[0144] In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 4As shown, the computer device includes a processor, memory, network interface, and database connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and database. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The network interface is used for communication with external terminals via a network connection. When the computer program is executed by the processor, it implements a book tag recognition method based on dot matrix technology and AI analysis.

[0145] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of a book tag recognition method based on dot matrix technology and AI analysis.

[0146] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements a book tag recognition method based on dot matrix technology and AI analysis.

[0147] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0148] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is used as an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0149] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A book tag recognition method based on dot matrix technology and AI analysis, characterized in that: Based on preset coding rules, the identity area, chapter area, and exercise area of ​​the book are coded in layers. When the coded information sent by the identification terminal is received, the coded information is identified to confirm the identity information of the student to whom the book belongs; After the identity information is identified, the grading information for the current chapter's exercises area is retrieved; When the completion of the current chapter's corrections is detected, the obtained correction information is associated with and stored along with the identity information and chapter information.

2. The book tag recognition method based on dot matrix technology and AI analysis according to claim 1, characterized in that, The identity area is set on the surface of the book. The step of performing layered encoding processing on the identity area, chapter area, and exercise area of ​​the book based on preset encoding rules includes: Based on the identity information of different students, coordinate regions corresponding to different identity information are pre-selected in a pre-constructed coordinate system; Within a selected single coordinate region, the coordinate region is divided into multiple coordinate sub-regions based on different chapter information; Within the selected coordinate sub-region, a portion of the coordinate range is subjected to dense coding processing, and the densely coded coordinate range is used as the exercise area.

3. The book tag recognition method based on dot matrix technology and AI analysis according to claim 1, characterized in that, The step of identifying the encoded information to confirm the book's identity information upon receiving the encoded information from the identification terminal includes: When the coded information sent by the recognition terminal is received, the coordinate data sequence representing the handwriting and the corresponding timestamp information in the coded information are obtained. Based on the coordinate data sequence and the corresponding timestamp information, determine whether to trigger an identity verification command; If so, then filter the identity information that matches the current coordinate data sequence from the preset student identity database.

4. The book tag recognition method based on dot matrix technology and AI analysis according to claim 3, characterized in that, The step of obtaining the grading information for the current chapter's exercises area after identity verification includes: When the correction information is received from the recognition terminal, the coordinate data sequence of the correction information and the corresponding timestamp information are recognized. Determine the coordinate sub-region to which the coordinate data sequence belongs and match the corresponding chapter information; The received coordinate data sequence and timestamp information are converted into handwriting information in the coordinate system in real time, and the handwriting information is pre-associated with the chapter information; When a change in the coordinate sub-region to which the coordinate data sequence belongs is detected, the handwriting information is associated with the changed new chapter information.

5. The book tag recognition method based on dot matrix technology and AI analysis according to claim 3, characterized in that, After the step of obtaining the grading information for the current chapter's exercises area after completing the identification of identity information, the method further includes: Determine whether the currently received handwriting information triggers an erasure or deletion command; If so, the target handwriting information to be deleted is determined based on the alteration recognition rules; Remove the association between the target handwriting information and the chapter information, and delete the target handwriting information along with the currently triggered handwriting information.

6. The book tag recognition method based on dot matrix technology and AI analysis according to claim 5, characterized in that, The step of determining whether the currently received handwriting information triggers an erasure or deletion command includes the following steps: Obtain the coordinate data sequence and timestamp information of the handwriting information, and send the coordinate data sequence and the corresponding timestamp information to the preset alteration handwriting recognition model; When the alteration handwriting recognition model receives a coordinate data sequence, it obtains handwriting information within a preset time period based on the timestamp information of the current coordinate data sequence. Determine whether the current coordinate data sequence overlaps with the coordinate data sequence within a preset time period, and obtain overlap information; The alteration handwriting recognition model is based on a pre-set alteration handwriting database. It identifies whether the current coordinate data sequence is an alteration handwriting and obtains the degree of matching of the alteration handwriting. Based on the overlap information and the degree of matching of the correction handwriting, it is determined whether the correction / deletion command should be triggered.

7. The book tag recognition method based on dot matrix technology and AI analysis according to claim 6, characterized in that, The step of determining the target handwriting information to be deleted based on the alteration recognition rules includes: The correction handwriting recognition model is based on overlap information to obtain coordinate points that overlap with the current coordinate data sequence; Based on timestamp information, determine the coordinate data sequence to which the overlapping coordinate points belong; The coordinate data sequence with more than a threshold number of overlapping coordinate points is used as the target handwriting information to be deleted.

8. A book tag recognition system based on dot matrix technology and AI analysis, characterized in that: The encoding processing module is used to perform layered encoding processing on the identity area, chapter area, and exercise area of ​​the book based on preset encoding rules; The identity recognition module is used to identify the coded information sent by the recognition terminal to confirm the identity information of the student to whom the book belongs. The grading recognition module is used to obtain the grading information of the current chapter's exercise area after the identity information has been recognized; The association module is used to associate and store the obtained correction information with the identity information and chapter information when the correction completion information of the current chapter is detected.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the book tag recognition method based on dot matrix technology and AI analysis as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the book tag recognition method based on dot matrix technology and AI analysis as described in any one of claims 1 to 7.

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