Handwriting track generation method and device, equipment and storage medium thereof

Abstract

The embodiment of the invention belongs to the technical field of biological recognition, is applied to a banking business security signature scene, and relates to a handwriting track generation method, device and equipment and a storage medium thereof.The method comprises the steps that fingertip initial position information and fingerprint image information are processed, and actual boundary position information and fingerprint features of the initial fingertip information are obtained; according to the actual boundary position information and the fingerprint features, generating a track starting point image on a handwriting track generation interface; fingertip position information is obtained in real time, and time sequence arrangement is carried out; target position boundaries corresponding to all fingertip position information are obtained after processing; and generating a handwriting track containing the fingerprint image according to the target position boundary and the fingerprint features. When the handwriting track generation method is applied to a business signature scene of a bank, identity signature can be carried out, and fingerprint feature information is introduced into the signature, so that a bank storage terminal can conveniently store the handwriting track and the fingerprint image as safety information, and the safety is higher.

Description

Technical Field

[0001] The present application relates to the field of biometric technology, and is applied to banking business security signature scenarios, and in particular to a handwriting trajectory generation method, device, equipment and storage medium thereof. Background Art

[0002] Handwriting recognition technology is an application of pattern recognition in the field of human-computer interaction. Handwriting recognition is divided into air handwriting recognition and plane handwriting recognition.

[0003] Plane handwriting recognition mainly uses RFID radio frequency system. In RFID system, passive RFID tags can backscatter wireless signals from the reader antenna. Therefore, the tag is usually attached to the pen tip to be tracked. The backscattered signal read by the reader can accurately track the movement trajectory of the target object. The data of aerial handwriting recognition currently mainly uses inertial sensor method, that is, the coordinate system corresponding to the inertial sensor reading rotates with the rotation of the inertial sensor to generate the handwriting trajectory. Although this method avoids the use of a stylus, the generated handwriting trajectory is not accurate enough. Especially in specific scenarios with high security requirements such as banks, a handwriting trajectory generation method with security performance is urgently needed. Summary of the invention

[0004] The purpose of the embodiments of the present application is to propose a handwriting trajectory generation method, device, equipment and storage medium thereof to solve the problem that the existing handwritten signature method cannot provide more security information in scenarios with specific high security requirements such as banking services.

[0005] In order to solve the above technical problems, the present application embodiment provides a handwriting trajectory generation method, which adopts the following technical solution:

[0006] A method for generating a handwriting trajectory comprises the following steps:

[0007] Identify the current prompt command of the target prompt interface;

[0008] If the current prompt instruction is a user input operation instruction, initial fingertip information of the target user is obtained according to a preset integrated sensor, wherein the integrated sensor includes a position sensor and a fingerprint sensor, and the initial fingertip information includes initial fingertip position information obtained by the position sensor and fingerprint image information obtained by the fingerprint sensor;

[0009] Inputting the fingertip initial position information and the fingerprint image information into a preset image processing model to obtain actual boundary position information and fingerprint features of the initial fingertip information, wherein the actual boundary position information is obtained by performing edge algorithm detection on the fingertip initial position information, and the fingerprint features are obtained by performing feature point detection on the fingerprint image information;

[0010] According to the actual boundary position information of the initial fingertip information and the fingerprint features, a fingerprint image is generated as a track starting point image in a preset handwriting track generation interface;

[0011] Acquire fingertip position information in real time, and use a preset real-time timer to set a first timestamp for the fingertip position information acquired in real time;

[0012] According to the first timestamp, all fingertip position information acquired in real time is time-sequentially sorted to obtain time-sequential fingertip position information;

[0013] Inputting the time-series fingertip position information into the image processing model to obtain the target position boundaries corresponding to all the fingertip position information respectively;

[0014] A handwriting trajectory including the fingerprint image is generated in the handwriting trajectory generation interface according to the target position boundary and the fingerprint feature.

[0015] Furthermore, the image processing model includes an image processing model based on the OpenCV algorithm, and the step of inputting the fingertip initial position information and the fingerprint image information into a preset image processing model to obtain the actual boundary position information and fingerprint features of the initial fingertip information specifically includes:

[0016] Inputting the fingertip initial position information and the fingerprint image information into the image processing model based on the OpenCV algorithm;

[0017] Performing edge detection on the initial fingertip position information by using the Canny edge detection algorithm in the image processing model based on the OpenCV algorithm to identify actual boundary position information of the initial fingertip information;

[0018] The fingerprint feature detection is performed on the fingerprint image information by using the feature point detection function in the image processing model based on the OpenCV algorithm to identify the fingerprint feature contained in the initial fingertip information.

[0019] Furthermore, the actual boundary position information is the actual boundary position information of the fingertip in the preset sensing frame, and the step of generating a fingerprint image as a track starting point image in a preset handwriting track generation interface according to the actual boundary position information of the initial fingertip information and the fingerprint feature specifically includes:

[0020] Adding the fingerprint feature to the actual boundary position to generate a first display image;

[0021] Identify the size ratio between the handwriting trajectory generation interface and the sensor frame through a preset interface configuration file;

[0022] If the size of the handwriting trajectory generation interface is consistent with that of the sensor frame, the first display image is directly displayed on the handwriting trajectory generation interface according to the actual boundary position of the first display image in the sensor frame to obtain the fingerprint image;

[0023] If the size of the handwriting trajectory generation interface is inconsistent with that of the sensor frame, the position information of the first display image in the handwriting trajectory generation interface is adjusted according to the size ratio between the handwriting trajectory generation interface and the sensor frame, and the first display image is scaled at the adjusted position information, and the second display image obtained after the scaling is displayed on the handwriting trajectory generation interface to obtain the fingerprint image.

[0024] Furthermore, the step of acquiring the fingertip position information in real time and setting a first timestamp for the fingertip position information acquired in real time using a preset real-time timer specifically includes:

[0025] The fingertip position information is acquired in real time through the position sensor, and the real-time timer is used to set a first timestamp for the real-time acquired fingertip position information, wherein the position sensor includes any one of a contact capacitive position sensor, a contact infrared position sensor, and a non-contact optical position sensor.

[0026] Furthermore, the step of inputting the time-series fingertip position information into the image processing model to obtain the target position boundaries corresponding to all the fingertip position information specifically includes:

[0027] Using the Canny edge detection algorithm to perform edge detection on all fingertip position information in the time-series fingertip position information to obtain edge detection results;

[0028] Determine the target position boundaries corresponding to all the fingertip position information respectively according to the edge detection result;

[0029] After executing the step of inputting the time-series fingertip position information into the image processing model to obtain the target position boundaries corresponding to all the fingertip position information, the method further includes:

[0030] According to the time series relationship, the target position boundaries corresponding to all the fingertip position information are compared;

[0031] If there are N consecutive fingertip position information corresponding to the target position boundary that is consistent, and the N consecutive fingertip position information is not the fingertip position information at the end of the sequence, then a prompt indicating that the input has a pause is displayed on the handwriting trajectory generation interface, where N is a positive integer greater than 1;

[0032] If there are N consecutive fingertip position information corresponding to the target position boundaries that are consistent, and the N consecutive fingertip position information is the fingertip position information at the end of the sequence, a continue input prompt or an input completion confirmation prompt is displayed on the handwriting trajectory generation interface.

[0033] Furthermore, the step of generating a handwriting trajectory including the fingerprint image in the handwriting trajectory generation interface according to the target position boundary and the fingerprint feature specifically includes:

[0034] According to the size ratio between the handwriting trajectory generation interface and the sensor frame, and in combination with the target position boundaries corresponding to all the fingertip position information in the sensor frame, a mapping image frame corresponding to all the fingertip position information is generated in the handwriting trajectory generation interface;

[0035] Adding the fingerprint features to the target position boundaries corresponding to all fingertip position information to generate a target display image set;

[0036] Uniformly scaling all display images in the target display image set to the size of the mapping image frame, and adding the scaled images one by one to the corresponding mapping image frames;

[0037] According to the timing information of all the fingertip position information, a dynamic interactive animation method is introduced to dynamically render the images in all the mapped image frames to obtain a handwriting track containing the fingerprint image.

[0038] Furthermore, the step of generating a handwriting trajectory including the fingerprint image in the handwriting trajectory generation interface according to the target position boundary and the fingerprint feature further includes:

[0039] Acquire fingerprint image information in real time through the fingerprint sensor, and use the real-time timer to set a second timestamp for the fingerprint image information acquired in real time, wherein the fingerprint sensor includes a contact capacitive fingerprint sensor or a non-contact optical fingerprint sensor;

[0040] According to the second timestamp, all fingerprint image information acquired in real time is time-sequentially sorted to obtain time-sequential fingerprint image information;

[0041] Inputting the time-series fingerprint image information into the image processing model, and extracting fingerprint features corresponding to all the fingerprint image information respectively;

[0042] Calculate the characteristic distance between the fingerprint features corresponding to all the fingerprint image information and the fingerprint features corresponding to the initial fingertip information, and obtain the characteristic distance calculation result;

[0043] If it is identified through the feature distance calculation result that M consecutive feature distance values ​​all exceed the set distance value, and the M feature distance values ​​are the feature distance values ​​corresponding to the last M fingerprint image information, a prompt to correct the input gesture is displayed on the handwriting trajectory generation interface, where M is a positive integer greater than 1.

[0044] In order to solve the above technical problems, the embodiment of the present application also provides a handwriting trajectory generation device, which adopts the following technical solution:

[0045] A handwriting trajectory generating device, comprising:

[0046] A prompt instruction recognition module is used to recognize the current prompt instruction of the target prompt interface;

[0047] An initial fingertip information acquisition module is used to acquire the initial fingertip information of the target user according to a preset integrated sensor if the current prompt instruction is a user input operation instruction, wherein the integrated sensor includes a position sensor and a fingerprint sensor, and the initial fingertip information includes the initial position information of the fingertip acquired by the position sensor and the fingerprint image information acquired by the fingerprint sensor;

[0048] The first image processing module is used to input the fingertip initial position information and the fingerprint image information into a preset image processing model to obtain the actual boundary position information and fingerprint features of the initial fingertip information, wherein the actual boundary position information is obtained by performing edge algorithm detection on the fingertip initial position information, and the fingerprint features are obtained by performing feature point detection on the fingerprint image information;

[0049] A trajectory starting point image generation module, used to generate a fingerprint image as a trajectory starting point image in a preset handwriting trajectory generation interface according to the actual boundary position information of the initial fingertip information and fingerprint features;

[0050] A real-time acquisition module, used for acquiring fingertip position information in real time, and using a preset real-time timer to set a first timestamp for the real-time acquired fingertip position information;

[0051] A time-sequencing arrangement module, used to perform time-sequencing arrangement on all fingertip position information acquired in real time according to the first timestamp, so as to obtain time-sequential fingertip position information;

[0052] The second image processing module is used to input the time-series fingertip position information into the image processing model to obtain the target position boundaries corresponding to all the fingertip position information respectively;

[0053] The fingerprint handwriting trajectory generation module is used to generate a handwriting trajectory including the fingerprint image in the handwriting trajectory generation interface according to the target position boundary and the fingerprint feature.

[0054] In order to solve the above technical problems, the embodiment of the present application further provides a computer device, which adopts the following technical solution:

[0055] A computer device comprises a memory and a processor, wherein the memory stores computer-readable instructions, and the processor implements the steps of the above-mentioned handwriting trajectory generation method when executing the computer-readable instructions.

[0056] In order to solve the above technical problems, the embodiment of the present application further provides a computer-readable storage medium, which adopts the following technical solution:

[0057] A computer-readable storage medium stores computer-readable instructions, and when the computer-readable instructions are executed by a processor, the steps of the handwriting trajectory generation method as described above are implemented.

[0058] Compared with the prior art, the embodiments of the present application have the following beneficial effects:

[0059] The handwriting trajectory generation method described in the embodiment of the present application processes the initial fingertip position information and fingerprint image information to obtain the actual boundary position information and fingerprint features of the initial fingertip information; generates a fingerprint image as the trajectory starting point image in the handwriting trajectory generation interface based on the actual boundary position information and fingerprint features; obtains fingertip position information in real time, and performs time-series sorting on all fingertip position information obtained in real time to obtain time-series fingertip position information; obtains the target position boundaries corresponding to all fingertip position information after processing; generates a handwriting trajectory containing the fingerprint image in the handwriting trajectory generation interface based on the target position boundaries and fingerprint features. The handwriting trajectory generation method described is applied to the business signature scenario of the bank, which not only enables identity signature, but also introduces fingerprint feature information in the signature, so that the bank storage terminal can save the handwriting trajectory and fingerprint image as security information together, which is more secure. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] In order to more clearly illustrate the scheme in the present application, a brief introduction is given below to the drawings required for use in the description of the embodiments of the present application. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0061] Figure 1 is an exemplary system architecture diagram to which the present application may be applied;

[0062] Figure 2 is a flow chart of an embodiment of a handwriting trajectory generation method according to the present application;

[0063] Figure 3 yes Figure 2 A flowchart of a specific embodiment of step 203 is shown;

[0064] Figure 4 yes Figure 2 A flowchart of a specific embodiment of step 204 is shown;

[0065] Figure 5 yes Figure 2 A flowchart of a specific embodiment of step 207 is shown;

[0066] Figure 6 yes Figure 2 A flowchart of a specific embodiment of step 208 is shown;

[0067] Figure 7 is a structural schematic diagram of an embodiment of a handwriting trajectory generating device according to the present application;

[0068] Figure 8 It is a structural diagram of an embodiment of a computer device according to the present application. DETAILED DESCRIPTION

[0069] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by technicians in the technical field of the present application; the terms used in the specification of the application herein are only for the purpose of describing specific embodiments and are not intended to limit the present application; the terms "including" and "having" and any variations thereof in the specification and claims of the present application and the above-mentioned drawings are intended to cover non-exclusive inclusions. The terms "first", "second", etc. in the specification and claims of the present application or the above-mentioned drawings are used to distinguish different objects, not to describe a specific order.

[0070] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0071] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the accompanying drawings.

[0072] like Figure 1 As shown, the system architecture 100 may include terminal devices 101, 102, 103, a network 104 and a server 105. The network 104 is used to provide a medium for communication links between the terminal devices 101, 102, 103 and the server 105. The network 104 may include various connection types, such as wired, wireless communication links or optical fiber cables, etc.

[0073] Users can use terminal devices 101, 102, 103 to interact with server 105 through network 104 to receive or send messages, etc. Various communication client applications can be installed on terminal devices 101, 102, 103, such as web browser applications, shopping applications, search applications, instant messaging tools, email clients, social platform software, etc.

[0074] The terminal devices 101, 102, and 103 can be various electronic devices with display screens and supporting web browsing, including but not limited to smart phones, tablet computers, e-book readers, MP3 players (Moving Picture Experts Group Audio Layer III), MP4 (Moving Picture Experts Group Audio Layer IV) players, laptop computers, desktop computers, etc.

[0075] The server 105 may be a server that provides various services, such as a background server that provides support for web pages displayed on the terminal devices 101 , 102 , and 103 .

[0076] It should be noted that the handwriting trajectory generation method provided in the embodiment of the present application is generally executed by a terminal device, and accordingly, the handwriting trajectory generation device is generally arranged in the terminal device.

[0077] It should be understood that Figure 1The number of terminal devices, networks and servers in the embodiment is only for illustration. Any number of terminal devices, networks and servers may be provided according to implementation requirements.

[0078] Continue to refer Figure 2 , shows a flow chart of an embodiment of a handwriting trajectory generation method according to the present application. The handwriting trajectory generation method comprises the following steps:

[0079] Step 201, identifying the current prompt instruction of the target prompt interface.

[0080] In this embodiment, the target prompt interface can also be a preset handwriting trajectory generation interface. By identifying the current prompt instruction of the target prompt interface, the purpose is to determine whether the handwriting input step has been performed according to the current prompt instruction, so as to guide the operating user to perform the next operation. The handwriting trajectory generation method is applied to the business signature scenario of the bank. At this time, the operating user can be a business processing user. In this signature scenario, not only can the identity signature be performed, but also the fingerprint feature information is introduced into the signature, which is more secure.

[0081] Step 202: If the current prompt instruction is a user input operation instruction, the initial fingertip information of the target user is obtained according to a preset integrated sensor, wherein the integrated sensor includes a position sensor and a fingerprint sensor, and the initial fingertip information includes the fingertip initial position information obtained by the position sensor and the fingerprint image information obtained by the fingerprint sensor.

[0082] The initial position information of the fingertip obtained by the position sensor and the fingerprint image information obtained by the fingerprint sensor facilitate subsequent combination with the image processing model to obtain the actual boundary position information and fingerprint features of the initial fingertip information.

[0083] Step 203, input the fingertip initial position information and the fingerprint image information into a preset image processing model to obtain the actual boundary position information and fingerprint features of the initial fingertip information, wherein the actual boundary position information is obtained by performing edge algorithm detection on the fingertip initial position information, and the fingerprint features are obtained by performing feature point detection on the fingerprint image information.

[0084] In this embodiment, the image processing model includes an image processing model based on the OpenCV algorithm.

[0085] Continue to refer Figure 3 , Figure 3 yes Figure 2 The flowchart of a specific embodiment of step 203 shown includes:

[0086] Step 301, inputting the fingertip initial position information and the fingerprint image information into the image processing model based on the OpenCV algorithm;

[0087] Step 302, performing edge detection on the initial fingertip position information by using the Canny edge detection algorithm in the image processing model based on the OpenCV algorithm, and identifying the actual boundary position information of the initial fingertip information;

[0088] Step 303: Perform fingerprint feature detection on the fingerprint image information by using a feature point detection function in the image processing model based on the OpenCV algorithm to identify the fingerprint features contained in the initial fingertip information.

[0089] Specifically, the feature point detection function in the image processing model based on the OpenCV algorithm includes a GoodFeaturesToTrack detection function built into the OpenCV algorithm, and the GoodFeaturesToTrack detection function is used to detect feature points in an image.

[0090] In this embodiment, an image processing model based on the OpenCV algorithm is used to process the initial fingertip position information and the fingerprint image information respectively, so as to obtain the actual boundary position information and fingerprint features of the initial fingertip information, and provide data support for the subsequent handwriting trajectory generation. In addition, the OpenCV algorithm integrates the image edge detection algorithm and the feature point detection algorithm, which can meet the handwriting trajectory generation in the banking business signature scenario.

[0091] Step 204 , generating a fingerprint image as a track starting point image in a preset handwriting track generation interface according to the actual boundary position information of the initial fingertip information and the fingerprint features.

[0092] In this embodiment, the actual boundary position information is the actual boundary position information of the fingertip in the preset sensor frame. Specifically, the preset sensor frame is, for example, a handwriting frame in which the above-mentioned position sensor and fingerprint sensor are set at the frame interface. The actual boundary position information of the fingertip in the preset sensor frame, for example, the coordinate position information of the fingertip in the sensor frame, can create a two-dimensional coordinate system based on the sensor frame, and any point in the sensor frame has corresponding horizontal and vertical coordinate information.

[0093] Continue to refer Figure 4 , Figure 4 yes Figure 2 The flowchart of a specific embodiment of step 204 shown includes:

[0094] Step 401, adding the fingerprint feature to the actual boundary position to generate a first display image;

[0095] Step 402, identifying the size ratio relationship between the handwriting trajectory generation interface and the sensor frame through a preset interface configuration file;

[0096] Step 403, if the size of the handwriting trajectory generation interface is consistent with that of the sensor frame, directly displaying the first display image on the handwriting trajectory generation interface according to the actual boundary position of the first display image in the sensor frame to obtain the fingerprint image;

[0097] Step 404: If the size of the handwriting trajectory generation interface is inconsistent with that of the sensor frame, the position information of the first display image in the handwriting trajectory generation interface is adjusted according to the size ratio between the handwriting trajectory generation interface and the sensor frame, and the first display image is scaled at the adjusted position information, and the second display image obtained after the scaling is displayed on the handwriting trajectory generation interface to obtain the fingerprint image.

[0098] In this embodiment, the position information of the first display image in the handwriting trajectory generation interface is adjusted according to the size ratio between the handwriting trajectory generation interface and the sensor frame. For example, the ratio between the handwriting trajectory generation interface and the sensor frame is 5:1, and the position information of the first display image in the sensor frame is a range area. Assuming that the range area is a rectangular area, the coordinate vertices of the rectangle are (2,10), (3,10), (2,12) and (3,12) respectively, and the coordinate unit is centimeters. Then, the position area is a 1cmx2cm fingerprint area, which is proportionally scaled to the handwriting trajectory generation interface. At this time, the corresponding position information in the handwriting trajectory generation interface is (10,50), (15,50), (10,60) and (15,60). At this time, the corresponding position area in the handwriting trajectory generation interface is a 5cmx10cm fingerprint area, that is, the synchronous update of the position area is achieved, and the proportional scaling of the fingerprint image is also achieved.

[0099] Step 205: acquiring fingertip position information in real time, and using a preset real-time timer to set a first timestamp for the fingertip position information acquired in real time.

[0100] In this embodiment, the step of acquiring fingertip position information in real time and using a preset real-time timer to set a first timestamp for the real-time acquired fingertip position information specifically includes: acquiring fingertip position information in real time through the position sensor, and using the real-time timer to set a first timestamp for the real-time acquired fingertip position information, wherein the position sensor includes any one of a contact capacitive position sensor, a contact infrared position sensor, and a non-contact optical position sensor.

[0101] By setting the first timestamp, it is convenient to perform time-series sorting on the fingertip position information acquired in real time according to the first timestamp, so that a handwriting trajectory can be generated in combination with the fingertip position change.

[0102] Step 206: According to the first timestamp, all fingertip position information acquired in real time is time-series sorted to obtain time-series fingertip position information.

[0103] Step 207: input the time-series fingertip position information into the image processing model to obtain the target position boundaries corresponding to all the fingertip position information.

[0104] Continue to refer Figure 5 , Figure 5 yes Figure 2 The flowchart of a specific embodiment of step 207 shown includes:

[0105] Step 501, using the Canny edge detection algorithm to perform edge detection on all fingertip position information in the time-series fingertip position information, to obtain edge detection results;

[0106] Step 502: Determine the target position boundaries corresponding to all the fingertip position information respectively according to the edge detection result.

[0107] Specifically, the Canny edge detection algorithm in the OpenCV algorithm may be used to perform edge detection on all the fingertip position information in the time-series fingertip position information to obtain edge detection results.

[0108] In this embodiment, after executing the step of inputting the timed fingertip position information into the image processing model to obtain the target position boundaries corresponding to all the fingertip position information, the method also includes: comparing the target position boundaries corresponding to all the fingertip position information according to the timed relationship; if there are N consecutive fingertip position information corresponding to the target position boundaries that are consistent, and the N consecutive fingertip position information are not the fingertip position information at the end of the sequence, then a pause prompt for input is displayed on the handwriting trajectory generation interface, where N is a positive integer greater than 1; if there are N consecutive fingertip position information corresponding to the target position boundaries that are consistent, and the N consecutive fingertip position information are the fingertip position information at the end of the sequence, then a continue input prompt or an input completion confirmation prompt is displayed on the handwriting trajectory generation interface.

[0109] Specifically, if there are N consecutive pieces of fingertip position information corresponding to the target position boundaries that are consistent, and the said N consecutive pieces of fingertip position information are not the fingertip position information at the end of the sequence, that is, the fingertip position information continuously acquired in real time is consistent, at this time, it is considered that there is a pause in the handwriting input, and the operating user is prompted; if there are N consecutive pieces of fingertip position information corresponding to the target position boundaries that are consistent, and the said N consecutive pieces of fingertip position information are the fingertip position information at the end of the sequence, there may be an input pause, or the input may have been completed, and a prompt is given to confirm the input completion.

[0110] Step 208: generating a handwriting trajectory including the fingerprint image in the handwriting trajectory generating interface according to the target position boundary and the fingerprint feature.

[0111] Continue to refer Figure 6 , Figure 6 yes Figure 2 The flowchart of a specific embodiment of step 208 shown includes:

[0112] Step 601, generating mapping image frames corresponding to all fingertip position information in the handwriting trajectory generation interface according to the size ratio relationship between the handwriting trajectory generation interface and the sensor frame, and combining the target position boundaries corresponding to all fingertip position information in the sensor frame;

[0113] Step 602, adding the fingerprint features to the target position boundaries corresponding to all fingertip position information, and generating a target display image set;

[0114] Step 603, uniformly scaling all display images in the target display image set to the size of the mapping image frame, and adding the scaled images one by one to the corresponding mapping image frames;

[0115] Step 604: According to the timing information of all the fingertip position information, a dynamic interactive animation method is introduced to dynamically render the images in all the mapped image frames to obtain a handwriting track containing the fingerprint image.

[0116] By uniformly scaling all display images in the target display image set to the size of the mapping image frame, adding the scaled images one by one to the corresponding mapping image frames, and introducing a dynamic interactive animation method to dynamically render the images in all mapping image frames based on the timing information of all fingertip position information, a handwriting trajectory containing the fingerprint image is obtained, and the dynamic trajectory containing the fingerprint image is generated in the handwriting trajectory generation interface, which is convenient for the bank storage terminal to save the handwriting trajectory and the fingerprint image as security information.

[0117] In this embodiment, the step of generating a handwriting trajectory including the fingerprint image in the handwriting trajectory generation interface according to the target position boundary and the fingerprint feature also includes: acquiring fingerprint image information in real time through the fingerprint sensor, and using the real-time timer to set a second timestamp for the fingerprint image information acquired in real time, wherein the fingerprint sensor includes a contact capacitive fingerprint sensor or a non-contact optical fingerprint sensor; according to the second timestamp, all fingerprint image information acquired in real time is time-sequenced to obtain time-sequenced fingerprint image information; inputting the time-sequenced fingerprint image information into the image processing model to extract fingerprint features corresponding to all fingerprint image information respectively; performing feature distance calculation on the fingerprint features corresponding to all fingerprint image information respectively and the fingerprint features corresponding to the initial fingertip information one by one to obtain a feature distance calculation result; if it is identified through the feature distance calculation result that M consecutive feature distance values ​​all exceed the set distance value, and the M feature distance values ​​are the feature distance values ​​corresponding to the last M fingerprint image information, then a prompt for correcting the input gesture is displayed on the handwriting trajectory generation interface, wherein M is a positive integer greater than 1.

[0118] Specifically, the fingerprint sensor acquires fingerprint image information in real time, with the purpose of extracting fingerprint features from the fingerprint image information, thereby identifying whether the handwriting input is completed and whether there are non-standard input gestures during the handwriting process, so as to promptly remind the user to correct it and ensure the handwriting input effect.

[0119] This application processes the initial fingertip position information and fingerprint image information to obtain the actual boundary position information and fingerprint features of the initial fingertip information; based on the actual boundary position information and fingerprint features, a fingerprint image is generated as the trajectory starting point image in the handwriting trajectory generation interface; the fingertip position information is acquired in real time, and all the fingertip position information acquired in real time is time-sequenced to obtain time-sequenced fingertip position information; after processing, the target position boundaries corresponding to all the fingertip position information are obtained; based on the target position boundaries and fingerprint features, a handwriting trajectory containing the fingerprint image is generated in the handwriting trajectory generation interface. The handwriting trajectory generation method is applied to the business signature scenario of the bank, which not only enables identity signature, but also introduces fingerprint feature information in the signature, so that the bank storage terminal can save the handwriting trajectory and fingerprint image as security information together, which is more secure.

[0120] The embodiments of the present application can acquire and process relevant data based on artificial intelligence technology. Artificial Intelligence (AI) is the theory, method, technology and application system that uses digital computers or machines controlled by digital computers to simulate, extend and expand human intelligence, perceive the environment, acquire knowledge and use knowledge to obtain the best results.

[0121] AI basic technologies generally include sensors, dedicated AI chips, cloud computing, distributed storage, big data processing technology, operation / interaction systems, mechatronics, etc. AI software technologies mainly include computer vision technology, robotics technology, biometrics technology, speech processing technology, natural language processing technology, and machine learning / deep learning.

[0122] In the embodiment of the present application, the actual boundary position information and fingerprint features of the initial fingertip information are obtained by processing the initial fingertip position information and the fingerprint image information; based on the actual boundary position information and the fingerprint features, a fingerprint image is generated as the trajectory starting point image in the handwriting trajectory generation interface; the fingertip position information is acquired in real time, and all the fingertip position information acquired in real time is time-sequenced to obtain time-sequenced fingertip position information; after processing, the target position boundaries corresponding to all the fingertip position information are obtained; based on the target position boundaries and the fingerprint features, a handwriting trajectory containing the fingerprint image is generated in the handwriting trajectory generation interface. The handwriting trajectory generation method is applied to the business signature scenario of the bank, which not only enables identity signature, but also introduces fingerprint feature information in the signature, so that the bank storage terminal can save the handwriting trajectory and fingerprint image as security information together, which is more secure.

[0123] Further references Figure 7 , as a response to the above Figure 2 In order to realize the method shown in the figure, the present application provides an embodiment of a handwriting trajectory generating device, and the device embodiment is Figure 2 Corresponding to the method embodiment shown, the device can be specifically applied to various electronic devices.

[0124] like Figure 7 As shown, the handwriting trajectory generation device 700 described in this embodiment includes: a prompt instruction recognition module 701, an initial fingertip information acquisition module 702, an image first processing module 703, a trajectory starting point image generation module 704, a real-time acquisition module 705, a time sequence arrangement module 706, an image second processing module 707 and a fingerprint handwriting trajectory generation module 708. Among them:

[0125] The prompt instruction recognition module 701 is used to recognize the current prompt instruction of the target prompt interface;

[0126] The initial fingertip information acquisition module 702 is used to acquire the initial fingertip information of the target user according to a preset integrated sensor if the current prompt instruction is a user input operation instruction, wherein the integrated sensor includes a position sensor and a fingerprint sensor, and the initial fingertip information includes the initial position information of the fingertip acquired by the position sensor and the fingerprint image information acquired by the fingerprint sensor;

[0127] The first image processing module 703 is used to input the fingertip initial position information and the fingerprint image information into a preset image processing model to obtain the actual boundary position information and fingerprint features of the initial fingertip information, wherein the actual boundary position information is obtained by performing edge algorithm detection on the fingertip initial position information, and the fingerprint features are obtained by performing feature point detection on the fingerprint image information;

[0128] The trajectory starting point image generating module 704 is used to generate a fingerprint image as a trajectory starting point image in a preset handwriting trajectory generating interface according to the actual boundary position information of the initial fingertip information and the fingerprint features;

[0129] A real-time acquisition module 705 is used to acquire fingertip position information in real time and use a preset real-time timer to set a first timestamp for the real-time acquired fingertip position information;

[0130] A time series arrangement module 706, configured to perform time series arrangement on all fingertip position information acquired in real time according to the first timestamp, to obtain time series fingertip position information;

[0131] The second image processing module 707 is used to input the time-series fingertip position information into the image processing model to obtain the target position boundaries corresponding to all the fingertip position information respectively;

[0132] The fingerprint handwriting trajectory generation module 708 is used to generate a handwriting trajectory including the fingerprint image in the handwriting trajectory generation interface according to the target position boundary and the fingerprint feature.

[0133] This application processes the initial fingertip position information and fingerprint image information to obtain the actual boundary position information and fingerprint features of the initial fingertip information; based on the actual boundary position information and fingerprint features, a fingerprint image is generated as the trajectory starting point image in the handwriting trajectory generation interface; the fingertip position information is acquired in real time, and all the fingertip position information acquired in real time is time-sequenced to obtain time-sequenced fingertip position information; after processing, the target position boundaries corresponding to all the fingertip position information are obtained; based on the target position boundaries and fingerprint features, a handwriting trajectory containing the fingerprint image is generated in the handwriting trajectory generation interface. The handwriting trajectory generation method is applied to the business signature scenario of the bank, which not only enables identity signature, but also introduces fingerprint feature information in the signature, so that the bank storage terminal can save the handwriting trajectory and fingerprint image as security information together, which is more secure.

[0134] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through computer-readable instructions, and the computer-readable instructions can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, the aforementioned storage medium can be a non-volatile storage medium such as a disk, an optical disk, a read-only memory (ROM), or a random access memory (RAM).

[0135] It should be understood that, although the steps in the flowchart of the accompanying drawings are displayed in sequence as indicated by the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least a part of the steps in the flowchart of the accompanying drawings may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be executed in turn or alternately with other steps or at least a part of the sub-steps or stages of other steps.

[0136] To solve the above technical problems, the present application also provides a computer device. Figure 8 , Figure 8 This is a basic structural block diagram of the computer device in this embodiment.

[0137] The computer device 8 includes a memory 8a, a processor 8b, and a network interface 8c that are interconnected through a system bus. It should be noted that the figure only shows a computer device 8 with a memory 8a, a processor 8b, and a network interface 8c, but it should be understood that it is not required to implement all the components shown, and more or fewer components can be implemented instead. Among them, those skilled in the art can understand that the computer device here is a device that can automatically perform numerical calculations and / or information processing according to pre-set or stored instructions, and its hardware includes but is not limited to a microprocessor, an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), a digital processor (DSP), an embedded device, etc.

[0138] The computer device may be a computing device such as a desktop computer, a notebook, a PDA, a cloud server, etc. The computer device may interact with a user through a keyboard, a mouse, a remote controller, a touch pad, or a voice control device.

[0139] The memory 8a includes at least one type of readable storage medium, and the readable storage medium includes flash memory, hard disk, multimedia card, card-type memory (for example, SD or DX memory, etc.), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic memory, disk, optical disk, etc. In some embodiments, the memory 8a can be an internal storage unit of the computer device 8, such as a hard disk or memory of the computer device 8. In other embodiments, the memory 8a can also be an external storage device of the computer device 8, such as a plug-in hard disk equipped on the computer device 8, a smart memory card (Smart Med ia Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc. Of course, the memory 8a can also include both the internal storage unit of the computer device 8 and its external storage device. In this embodiment, the memory 8a is generally used to store the operating system and various application software installed on the computer device 8, such as a computer-readable instruction of a handwriting trajectory generation method, etc. In addition, the memory 8a can also be used to temporarily store various types of data that have been output or are to be output.

[0140] The processor 8b may be a central processing unit (CPU), a controller, a microcontroller, a microprocessor, or other data processing chips in some embodiments. The processor 8b is generally used to control the overall operation of the computer device 8. In this embodiment, the processor 8b is used to run the computer-readable instructions or process data stored in the memory 8a, such as the computer-readable instructions for running the handwriting trajectory generation method.

[0141] The network interface 8c may include a wireless network interface or a wired network interface. The network interface 8c is generally used to establish a communication connection between the computer device 8 and other electronic devices.

[0142] The computer device proposed in this embodiment belongs to the field of biometric technology and is applied to the banking business security signature scenario. This application obtains the actual boundary position information and fingerprint features of the initial fingertip information by processing the initial fingertip position information and the fingerprint image information; generates a fingerprint image as the trajectory starting point image in the handwriting trajectory generation interface according to the actual boundary position information and the fingerprint features; obtains the fingertip position information in real time, and performs time-series sorting on all the fingertip position information obtained in real time to obtain the time-series fingertip position information; obtains the target position boundaries corresponding to all the fingertip position information after processing; generates a handwriting trajectory containing the fingerprint image in the handwriting trajectory generation interface according to the target position boundary and the fingerprint features. The handwriting trajectory generation method is applied to the business signature scenario of the bank, which can not only perform identity signature, but also introduce fingerprint feature information in the signature, so that the bank storage terminal can save the handwriting trajectory and fingerprint image as security information together, which is more secure.

[0143] The present application also provides another implementation, namely, providing a computer-readable storage medium, wherein the computer-readable storage medium stores computer-readable instructions, and the computer-readable instructions can be executed by a processor to enable the processor to perform the steps of the handwriting trajectory generation method as described above.

[0144] The computer-readable storage medium proposed in this embodiment belongs to the field of biometric technology and is applied to the banking business security signature scenario. This application obtains the actual boundary position information and fingerprint features of the initial fingertip information by processing the initial fingertip position information and the fingerprint image information; generates a fingerprint image as the trajectory starting point image in the handwriting trajectory generation interface according to the actual boundary position information and the fingerprint features; obtains the fingertip position information in real time, and performs time-series sorting on all the fingertip position information obtained in real time to obtain the time-series fingertip position information; obtains the target position boundaries corresponding to all the fingertip position information after processing; generates a handwriting trajectory containing the fingerprint image in the handwriting trajectory generation interface according to the target position boundary and the fingerprint features. The handwriting trajectory generation method is applied to the business signature scenario of the bank, which can not only perform identity signature, but also introduce fingerprint feature information in the signature, so that the bank storage terminal can save the handwriting trajectory and fingerprint image as security information together, which is more secure.

[0145] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes a number of instructions for a terminal device (which can be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in each embodiment of the present application.

[0146] Obviously, the embodiments described above are only some embodiments of the present application, rather than all embodiments. The preferred embodiments of the present application are given in the accompanying drawings, but they do not limit the patent scope of the present application. The present application can be implemented in many different forms. On the contrary, the purpose of providing these embodiments is to make the understanding of the disclosure of the present application more thorough and comprehensive. Although the present application is described in detail with reference to the aforementioned embodiments, for those skilled in the art, it is still possible to modify the technical solutions recorded in the aforementioned specific implementation methods, or to perform equivalent replacement of some of the technical features therein. Any equivalent structure made using the contents of the specification and drawings of this application, directly or indirectly used in other related technical fields, is similarly within the scope of patent protection of this application.

Claims

1. A handwriting trajectory generation method, characterized in that: The steps include: Identify the current prompt command of the target prompt interface; If the current prompt instruction is a user input operation instruction, initial fingertip information of the target user is obtained according to a preset integrated sensor, wherein the integrated sensor includes a position sensor and a fingerprint sensor, and the initial fingertip information includes initial fingertip position information obtained by the position sensor and fingerprint image information obtained by the fingerprint sensor; Inputting the fingertip initial position information and the fingerprint image information into a preset image processing model to obtain actual boundary position information and fingerprint features of the initial fingertip information, wherein the actual boundary position information is obtained by performing edge algorithm detection on the fingertip initial position information, and the fingerprint features are obtained by performing feature point detection on the fingerprint image information; According to the actual boundary position information of the initial fingertip information and the fingerprint features, a fingerprint image is generated as a track starting point image in a preset handwriting track generation interface; Acquire fingertip position information in real time, and use a preset real-time timer to set a first timestamp for the fingertip position information acquired in real time; According to the first timestamp, all fingertip position information acquired in real time is time-sequentially sorted to obtain time-sequential fingertip position information; Inputting the time-series fingertip position information into the image processing model to obtain the target position boundaries corresponding to all the fingertip position information respectively; A handwriting trajectory including the fingerprint image is generated in the handwriting trajectory generation interface according to the target position boundary and the fingerprint feature.

2. The handwriting trajectory generation method according to claim 1, characterized in that: The image processing model includes an image processing model based on the OpenCV algorithm. The step of inputting the fingertip initial position information and the fingerprint image information into a preset image processing model to obtain the actual boundary position information and fingerprint features of the initial fingertip information specifically includes: Inputting the fingertip initial position information and the fingerprint image information into the image processing model based on the OpenCV algorithm; Performing edge detection on the initial fingertip position information by using the Canny edge detection algorithm in the image processing model based on the OpenCV algorithm to identify actual boundary position information of the initial fingertip information; The fingerprint feature detection is performed on the fingerprint image information by using the feature point detection function in the image processing model based on the OpenCV algorithm to identify the fingerprint feature contained in the initial fingertip information.

3. The handwriting trajectory generation method according to claim 1, characterized in that: The actual boundary position information is the actual boundary position information of the fingertip in the preset sensor frame, and the step of generating a fingerprint image as a track starting point image in a preset handwriting track generation interface according to the actual boundary position information of the initial fingertip information and the fingerprint feature specifically includes: Adding the fingerprint feature to the actual boundary position to generate a first display image; Identify the size ratio between the handwriting trajectory generation interface and the sensor frame through a preset interface configuration file; If the size of the handwriting trajectory generation interface is consistent with that of the sensor frame, the first display image is directly displayed on the handwriting trajectory generation interface according to the actual boundary position of the first display image in the sensor frame to obtain the fingerprint image; If the size of the handwriting trajectory generation interface is inconsistent with that of the sensor frame, the position information of the first display image in the handwriting trajectory generation interface is adjusted according to the size ratio between the handwriting trajectory generation interface and the sensor frame, and the first display image is scaled at the adjusted position information, and the second display image obtained after the scaling is displayed on the handwriting trajectory generation interface to obtain the fingerprint image.

4. The handwriting trajectory generation method according to claim 1, characterized in that: The step of acquiring fingertip position information in real time and using a preset real-time timer to set a first timestamp for the fingertip position information acquired in real time specifically includes: The fingertip position information is acquired in real time through the position sensor, and the real-time timer is used to set a first timestamp for the real-time acquired fingertip position information, wherein the position sensor includes any one of a contact capacitive position sensor, a contact infrared position sensor, and a non-contact optical position sensor.

5. The handwriting trajectory generation method according to claim 1 or 2, characterized in that: The step of inputting the time-series fingertip position information into the image processing model to obtain the target position boundaries corresponding to all the fingertip position information specifically includes: Using the Canny edge detection algorithm to perform edge detection on all fingertip position information in the time-series fingertip position information to obtain edge detection results; Determine the target position boundaries corresponding to all the fingertip position information respectively according to the edge detection result; After executing the step of inputting the time-series fingertip position information into the image processing model to obtain the target position boundaries corresponding to all the fingertip position information, the method further includes: According to the time series relationship, the target position boundaries corresponding to all the fingertip position information are compared; If there are N consecutive fingertip position information corresponding to the target position boundary that is consistent, and the N consecutive fingertip position information is not the fingertip position information at the end of the sequence, then a prompt indicating that the input has a pause is displayed on the handwriting trajectory generation interface, where N is a positive integer greater than 1; If there are N consecutive fingertip position information corresponding to the target position boundaries that are consistent, and the N consecutive fingertip position information is the fingertip position information at the end of the sequence, a continue input prompt or an input completion confirmation prompt is displayed on the handwriting trajectory generation interface.

6. The handwriting trajectory generation method according to claim 3, characterized in that: The step of generating a handwriting trajectory including the fingerprint image in the handwriting trajectory generation interface according to the target position boundary and the fingerprint feature specifically includes: According to the size ratio between the handwriting trajectory generation interface and the sensor frame, and in combination with the target position boundaries corresponding to all the fingertip position information in the sensor frame, a mapping image frame corresponding to all the fingertip position information is generated in the handwriting trajectory generation interface; Adding the fingerprint features to the target position boundaries corresponding to all fingertip position information to generate a target display image set; Uniformly scaling all display images in the target display image set to the size of the mapping image frame, and adding the scaled images one by one to the corresponding mapping image frames; According to the timing information of all the fingertip position information, a dynamic interactive animation method is introduced to dynamically render the images in all the mapped image frames to obtain a handwriting track containing the fingerprint image.

7. The handwriting trajectory generation method according to claim 1 or 6, characterized in that: The step of generating a handwriting trajectory including the fingerprint image in the handwriting trajectory generation interface according to the target position boundary and the fingerprint feature further includes: Acquire fingerprint image information in real time through the fingerprint sensor, and use the real-time timer to set a second timestamp for the fingerprint image information acquired in real time, wherein the fingerprint sensor includes a contact capacitive fingerprint sensor or a non-contact optical fingerprint sensor; According to the second timestamp, all fingerprint image information acquired in real time is time-sequentially sorted to obtain time-sequential fingerprint image information; Inputting the time-series fingerprint image information into the image processing model, and extracting fingerprint features corresponding to all the fingerprint image information respectively; Calculate the characteristic distance between the fingerprint features corresponding to all the fingerprint image information and the fingerprint features corresponding to the initial fingertip information, and obtain the characteristic distance calculation result; If it is identified through the feature distance calculation result that M consecutive feature distance values ​​all exceed the set distance value, and the M feature distance values ​​are the feature distance values ​​corresponding to the last M fingerprint image information, a prompt to correct the input gesture is displayed on the handwriting trajectory generation interface, where M is a positive integer greater than 1.

8. A handwriting trajectory generating device, characterized in that: include: A prompt instruction recognition module is used to recognize the current prompt instruction of the target prompt interface; An initial fingertip information acquisition module is used to acquire the initial fingertip information of the target user according to a preset integrated sensor if the current prompt instruction is a user input operation instruction, wherein the integrated sensor includes a position sensor and a fingerprint sensor, and the initial fingertip information includes the initial position information of the fingertip acquired by the position sensor and the fingerprint image information acquired by the fingerprint sensor; The first image processing module is used to input the fingertip initial position information and the fingerprint image information into a preset image processing model to obtain the actual boundary position information and fingerprint features of the initial fingertip information, wherein the actual boundary position information is obtained by performing edge algorithm detection on the fingertip initial position information, and the fingerprint features are obtained by performing feature point detection on the fingerprint image information; A trajectory starting point image generation module, used to generate a fingerprint image as a trajectory starting point image in a preset handwriting trajectory generation interface according to the actual boundary position information of the initial fingertip information and fingerprint features; A real-time acquisition module, used for acquiring fingertip position information in real time, and using a preset real-time timer to set a first timestamp for the real-time acquired fingertip position information; A time-sequencing arrangement module, used to perform time-sequencing arrangement on all fingertip position information acquired in real time according to the first timestamp, so as to obtain time-sequential fingertip position information; The second image processing module is used to input the time-series fingertip position information into the image processing model to obtain the target position boundaries corresponding to all the fingertip position information respectively; The fingerprint handwriting trajectory generation module is used to generate a handwriting trajectory including the fingerprint image in the handwriting trajectory generation interface according to the target position boundary and the fingerprint feature.

9. A computer device, characterized in that: The method comprises a memory and a processor, wherein the memory stores computer-readable instructions, and the processor implements the steps of the handwriting trajectory generation method according to any one of claims 1 to 7 when executing the computer-readable instructions.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-readable instructions, and when the computer-readable instructions are executed by a processor, the steps of the handwriting trajectory generation method according to any one of claims 1 to 7 are implemented.

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