Electronic handwriting echoing method containing time sequence information, equipment and storage medium

Abstract

The invention discloses an electronic handwriting echoing method containing time sequence information and an electronic handwriting echoing method containing writing information, which comprises the following steps of: sampling an electronic signature in real time to obtain a series of sampling point sequences containing signature time sequence characteristic information, mapping sampling points into gray values, and filling line segments between adjacent sampling points with related gray values, drawing to obtain an electronic signature grey-scale map; and obtaining a visual electronic signature according to the grey-scale map. The defects that in a binary echo mode, image information is lost, and more valuable information cannot be obtained from an image for handwriting recognition and identification and the like are overcome.

Description

Technical Field

[0001] The present invention relates to the technical fields of artificial intelligence and information processing, and particularly to an electronic signature echo method including timing information. Background Art

[0002] If one wants to observe an electronic signature, it is undoubtedly the most intuitive method to echo the electronic signature as an image. The usual echo method is to connect each sampling point of the time series with a straight line of the same color to form a binary image (black background with white characters or white background with black characters).

[0003] An electronic signature is a sequence containing time information. In handwriting comparison, the timing information (including: the stroke order and the direction of the stroke) contained in the time series is a very valuable feature. For example, in handwriting identification, the expert needs to observe the stroke order and the writing direction of the handwriting to examine the writing habits of the writer, which is one of the bases for handwriting identification. However, under the limitation of binary echo, such valuable writing handwriting feature information such as timing cannot be directly obtained from the image.

[0004] Publication No. CN105405159A, titled "A Display Method and Device for Handwriting", provides a display method for handwriting. It collects the handwriting parameters generated by a continuous handwriting, and the handwriting parameters at least include the coordinates of multiple sampling points on the handwriting and the writing force; calculates the width of the handwriting at each sampling point according to the writing force; and draws and displays the graph corresponding to the handwriting according to the width of each sampling point. It can truly display the outline of the user's handwriting and achieve a good handwriting display effect. This method maps the pressure information in the electronic signature into the width of the sampling point strokes, so that the pressure information of the handwriting can be reflected in the image. However, it still cannot reflect the important timing information in the electronic signature and cannot determine the writing order and direction of the writing strokes.

[0005] Publication No. CN116612538A, titled "An Online Confirmation Method for Electronic Contract Content", obtains the overall feature histogram by extracting the distribution of the gray value change features of the data points in the handwritten font, obtains the local feature matrix by extracting the quantity distribution features of the data points corresponding to all data points in the preset neighborhood range of the handwritten font, and obtains the electronic signature recognition result according to the correlation between the overall feature histogram and the local feature matrix between the real-time handwritten font and the preset standard handwritten font. This method proposes a feature extraction method for handwritten fonts for electronic signature recognition in electronic contracts, and it does not describe the image echo method of the signature image used in the process and cannot reflect the timing information in the signature image. Summary of the Invention

[0006] In view of this, in view of the fact that the prior art does not reflect the timing characteristics contained in the electronic signature echo image and cannot determine the writing order and direction of the writing strokes, the present invention proposes an electronic signature echo method including timing information, which solves the deficiencies in the binary echo method such as image information loss and inability to obtain more valuable information from the image for handwriting recognition, identification, etc.

[0007] Based on the first aspect of the present application, an electronic handwriting echo method including timing information is proposed, including: real-time sampling of an electronic signature to obtain a series of sampling point sequences containing signature timing characteristic information, mapping the sampling points into gray values with timing information respectively, and filling the line segments between adjacent sampling points with relevant gray values, and drawing a gray scale image with timing information; obtaining a visual electronic signature according to the gray scale image.

[0008] Further preferably, the mapping of the sampling points into gray values includes: assigning an initial gray value to the first sampling point of the sequence, and constructing a mapping relationship according to the current sampling point time t i , the initial time t0 of the signature starting to write, and the initial gray value g(x0, y0):

[0009]

[0010] Calculating the gray value g(x i , y i ) of any point (x i , y i ) in the stroke trajectory sampling points.

[0011] Further preferably, the mapping of the sampling points into gray values includes: presetting corresponding gray values for all possible time values t of the sampling points of the electronic signature, constructing a look-up table (LUT), and obtaining the gray values of each sampling point through the look-up table according to the position of the sampling point: g(x i , y i ) = LUT(t i ).

[0012] Interpolating to fill the gray values of the line segments between adjacent sampling points, specifically including: according to the gray values g(p i ), g(p i+1 ) of adjacent sampling points and the Euclidean distance between the sampling points, calling the formula:

[0013]

[0014] Calculating the gray value g(p) of any point p on the inserted connection line segment, where d(p, p i ), d(p i+1 , p i ) are the distances from any point on the filled stroke segment to the i-th sampling point and the adjacent sampling points, d(pi+1 , p i ) is the gray value between adjacent sampling points, and a gray-scale map of the signature trajectory is drawn.

[0015] Further preferably, the gray value of the stroke segment between sampling points is filled with the extreme value, and the gray value of any one of the two adjacent sampling points (g(p i ) or g(p i+1 )) is used to fill the gray value of the connecting line segment therebetween, and a gray-scale map of the signature trajectory is drawn.

[0016] Further preferably, the gray value of the stroke segment between sampling points is filled with the average gray value. The arithmetic mean of the gray values of adjacent sampling points is used as the gray value for filling the connecting stroke segment, and a gray-scale map of the signature trajectory is drawn.

[0017] Further preferably, the minimum pixel value G min and the maximum pixel value G max in the gray-scale map G after visualization are set, the minimum non-zero gray value g min and the maximum gray value g max in the drawn gray-scale map are obtained, and the formula:

[0018]

[0019] is called to calculate the visualized gray value G(p) of any point p in the electronic signature handwriting gray-scale map, where g(p) is the gray value of point p in the obtained drawn gray-scale map, and an electronic signature visualized gray-scale map containing writing time sequence information is obtained.

[0020] Further, the gray-scale map is mapped into an RGB image through a look-up table, and an electronic signature trajectory image containing writing time sequence information is obtained.

[0021] According to another aspect of the present application, an electronic device is provided, including: a processor; and a memory storing a program, wherein the program includes instructions that, when executed by the processor, cause the processor to execute the above-mentioned electronic handwriting echo method including writing time sequence information.

[0022] According to another aspect of the present application, a non-transitory computer-readable storage medium storing computer instructions is provided, wherein the computer instructions are used to cause the computer to execute the electronic handwriting echo method including writing time sequence information according to any one of the above.

[0023] In view of the echo process of electronic signatures, the present invention maps the electronic signature features including timing information into the gray values of the strokes in the image, which can not only reflect the coordinate position and pressure information of the handwriting, but also reflect the timing information of the signature writing. By mapping the sampling points of the electronic signature sequences of different time series into different gray values, the echoed electronic signature image can contain timing information. The electronic signature echo image containing timing information can directly support handwriting identification by forensic experts and also support the application of downstream algorithms. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 Schematic flowchart of the echo display of electronic handwriting containing writing information in this exemplary embodiment;

[0025] Figure 2 Schematic flowchart of the gray-scale visualization process of the signature information in this exemplary embodiment;

[0026] Figure 3 Example diagram of the echoed electronic signature;

[0027] Figure 4 Block diagram of the exemplary electronic device that can be used to implement the embodiments of the present application. DETAILED DESCRIPTION

[0028] Embodiments of the present application will be described in more detail below with reference to the accompanying drawings. Although some embodiments of the present application are shown in the drawings, it should be understood that the present application can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. On the contrary, these embodiments are provided to more thoroughly and completely understand the present application. It should be understood that the drawings and embodiments of the present application are only for exemplary purposes and are not used to limit the protection scope of the present application.

[0029] It should be understood that the steps recited in the method embodiments of the present application can be executed in different orders and / or in parallel. In addition, the method embodiments may include additional steps and / or omit the steps shown. The scope of the present application is not limited in this regard.

[0030] As used herein, the term "including" and its variations are open-ended, i.e., "including but not limited to". The term "based on" means "at least partially based on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments". The relevant definitions of other terms will be given in the following description. It should be noted that the concepts of "first", "second", etc. mentioned in the present application are only used to distinguish different devices, modules or units, and are not used to limit the order of the functions executed by these devices, modules or units or their interdependencies.

[0031] It should be noted that the modifiers "one" and "multiple" mentioned in this application are illustrative rather than restrictive. Those skilled in the art should understand that, unless otherwise clearly specified in the context, it should be understood as "one or more".

[0032] The names of the messages or information exchanged between multiple devices in the embodiments of this application are only for illustrative purposes and are not used to limit the scope of these messages or information.

[0033] As Figure 1 shown in the schematic flowchart of the electronic handwriting echo method including timing information in the exemplary embodiment of this application. First, collect the information of the electronic signature writing trajectory points to obtain the time series data of the electronic signature stroke trajectory; then perform gray mapping on the features to be echoed in the time series data (such as time, pressure); then calculate the gray value based on each handwriting sampling point, draw the stroke trajectory using line segments to connect between the sampling points, and assign a gray value to each connected line segment; finally, map the calculated gray ratio into pixel values observable by the human eye to complete the image echo of the electronic signature.

[0034] Collect the position coordinates of the electronic signature trajectory and the signature moment, and sort them in the order of writing time. The obtained electronic signature time series is expressed as:

[0035] S = [(x0, y0, t0), (x1, y1, t1), …, (x n , y n , t n )],

[0036] where (x i , y i ) respectively represent the abscissa value and ordinate value of the electronic signature handwriting sampling point sequence at time t i , and for all t, there is t i < t i+1 . Echo the electronic signature handwriting containing time information as an electronic signature image. In the echoed image, the sampling points of the electronic signature stroke trajectory are arranged in the order of writing time. The purpose is to use a mapping to map the signature sequence time value into a gray value and map the time value of each sampling point of the electronic signature trajectory into the gray value of the corresponding sampling point. Reflect the information that was not originally reflected in the image in the image through a certain method.

[0037] That is:

[0038] f: t → g

[0039] Among them, t is the time value of each sampling point in the electronic signature sequence, and g is the gray value of the corresponding sampling point after mapping. To ensure that the magnitude relationship of the eigenvalue remains unified before and after mapping, this mapping should satisfy monotonicity, that is, g increases or decreases monotonically with t.

[0040] The mapping method of the present invention can be extended to other point features of the electronic signature in addition to mapping the timing information t to the grayscale image, such as the pressure information of the point, the speed information of the point, the pen-holding angle information, etc., as long as it is a point feature related to the sequence points. The mapping principle is the same as that of the time information. To ensure that the magnitude relationship of the eigenvalue remains unified before and after mapping, the mapping only needs to satisfy monotonicity. Satisfying monotonicity is to ensure that the magnitude relationship of the eigenvalue remains unified before and after mapping.

[0041] It is also possible to map a combination of multiple feature information. However, considering the readability of people, the exemplary embodiments of this application take the mapping of a single feature information as an example for further illustration.

[0042] Embodiment 1: One of the mapping methods can be: calculating a gray value for each sampling point according to the sampling time t. For example, assuming that the background gray value is 0 and an arbitrary initial gray value g0 is assigned to the first sampling point of the sequence, that is, g(x0, y0) = g0, according to the current sampling point time t i , the initial time t0 of the signature start writing, and the initial gray value g(x0, y0), construct the mapping relationship:

[0043]

[0044] Calculate the gray value g(x i , y i ) of any point (x i , y i ) on the stroke trajectory. Thus, the gray values of all sampling points in the electronic signature stroke trajectory sequence are obtained. It should be noted that this embodiment only exemplifies one way of mapping. In fact, any mapping that satisfies monotonicity can be used. According to this embodiment, the sampling points whose writing time is closer to the starting point have smaller gray values after mapping, and finally the result reflected in the image is lighter in color; while the sampling points whose time is farther from the starting point have larger gray values after mapping, and finally the result reflected in the image is darker in color. Due to the difference in color depth, the human eye can easily see the writing order of the strokes, which is a feature that binary echo does not have. It is also possible that the longer the writing duration, the smaller the gray value, as long as monotonicity is satisfied.

[0045] Embodiment 2: Preset the corresponding gray value g for the time value t of the electronic signature sampling point, construct a look-up table (LUT), and obtain the gray values of each sequence sampling point through the look-up table according to the position of the sampling point:

[0046] g(x i ,y i )=LUT(t i )

[0047] Example 3: Gray mapping is performed on features such as the pressure, speed, and angle of an electronic signature. Among them, let f represent the features of the electronic signature, such as the pressure feature, the speed feature, or the angle feature. One way is to use the identity mapping to map the feature f into a gray value (the identity mapping satisfies the aforementioned monotonicity):

[0048] g(x i ,y i )=f i

[0049] That is, the gray value g(x i ,y i ) of the point (x i ,y i ) is the eigenvalue corresponding to this point. It should be noted that any mapping that satisfies the aforementioned monotonicity can be used, not limited to the identity mapping.

[0050] It is also possible to further add time information to the gray value after performing gray mapping on the above-mentioned pressure, speed, and angle.

[0051] Draw a gray-scale image. After calculating the gray value of each handwriting sampling point, use line segments to connect the sampling points to draw a trajectory. For the purpose of echo display, assign a gray value to the connecting line segments, and the echo image contains corresponding handwriting feature information.

[0052] For the convenience of description, hereinafter, p i is used to represent (x i ,y i ). Then g(p i )=g(x i ,y i ) represents the gray value of the handwriting point (x i ,y i ), and the feature mapping into the gray value is completed. Usually, between two adjacent sampling points, the gray values of the two sampling points are used to calculate the gray values of each point on the line segment between the two sampling points, and used as the gray value filling of the line segment.

[0053] More specifically, if p i and p i+1 are two adjacent sampling points in time, it is necessary to connect p i and p i+1 with a line segment at the image layer. The gray value of this connecting line segment can be filled with the gray value of the connecting line segment by means of interpolation filling, extreme value filling, mean value filling, etc. For example, let p=(x, y) be from p i to p i+1For a point on the connecting line segment path, the grayscale value of point p can be the grayscale value of any one of two adjacent sampling points (g(p i )) or g(p i+1 )) for filling. An intermediate grayscale value can be calculated based on g(p i ) and g(p i+1 ) for filling.

[0054] The following is an example to illustrate the method of using interpolation filling to fill the grayscale of the points inserted between adjacent points. Specifically,

[0055] Example 1: For any two points p i to p j , the Euclidean distance between the two points can be calculated according to the formula:

[0056]

[0057] Thus, let p = (x, y) be any point on the connecting line segment between adjacent sampling points p i to p i+1 . Calculate the Euclidean distance between p i and p i+1 as d(p i , p i+1 ), and the Euclidean distance d(p, p i ) between p and p i . According to the sampling point distance and the grayscale values of adjacent sampling points, call the formula:

[0058]

[0059] to calculate the grayscale value of point p on the inserted connecting line segment.

[0060] The advantage of interpolation filling is that the granularity of the filled pixel values of the strokes is finer, and the visual perception of the human eye is better after echoing into an image. The disadvantage is that the position information of the starting and ending points of each stroke may be lost, and the point positions cannot be restored from the image.

[0061] For filling the strokes between sampling points, extreme value filling can also be used. The advantage of extreme value filling is that it can retain the position information of the starting and ending points of each stroke, that is, the position information of each sampling point, and the electronic signature sampling point data sequence can be restored from the echoed signature image; the disadvantage is that the visual perception of the echoed image is not as good as that of interpolation filling.

[0062] For the grayscale value g(p) filled between adjacent sampling points, the grayscale value of any one of the previous and next sampling points (g(p i )) or g(p i+1 )) is used for filling, that is,

[0063] g(p) = g(pi ) or: g(p) = g(p i+1 )

[0064] According to the constructed mapping relationship, since the gray value g increases or decreases monotonically with time t, thus g(p i ) or g(p i+1 ) is the gray value extreme on the path from the p i point to the p i+1 point.

[0065] Embodiment 3: Further, the gray values filled between adjacent sampling points can adopt mean filling. In mean filling, the arithmetic mean of the gray values of adjacent sampling points is calculated as the filled gray value. According to adjacent sampling points p i and p i+1 , the formula is called:

[0066] to calculate the mean-filled gray value.

[0067] The advantage of mean filling is that it can retain the position information of the starting point and the ending point of each stroke, that is, the position information of each sampling point. Therefore, it can be restored from the echoed image into a sampling point sequence. The disadvantage is that the visual effect of the echoed image is not as good as that of interpolation filling and is similar to extreme value filling. For all pixel points on the path from adjacent sampling points p i to p i+1 , they are filled according to the above-mentioned one method or a combination of multiple methods, and then the line segment from sampling point p i to p i+1 can be drawn. By traversing all sampling points of the electronic signature sequence and drawing the line segments between every two adjacent points in time, the echoed image of the entire signature can be obtained.

[0068] It should be noted that the filling method is not limited to the above examples, and different filling methods can be selected according to actual needs. For example, if only a rough observation of the feature changes is needed, extreme value filling or mean filling can be selected; while if the time sequence information of the signature needs to be fully reflected, interpolation filling is preferably selected. By performing real-time sampling on the electronic signature, a series of data sequences containing feature information such as signature time, pressure, position, speed, acceleration, and angular velocity are obtained. The sampling points are mapped to gray values, and the line segments between the sampling points are filled with relevant gray values to draw the gray-scale image of the electronic signature.

[0069] The drawn gray-scale image cannot be directly displayed as an image observable by the human eye because the data form used by the computer to represent the image is an 8-bit unsigned integer. Only when the image is stored in the form of integers with pixel values between 0 - 255 can it be directly visualized. Therefore, in order for the human eye to observe the image, a visualization conversion of the gray-scale image is required.

[0070] The following uses a specific example to illustrate the method of visualizing the grayscale image of the electronic signature trajectory. Sample the electronic signature stroke trajectory points according to time and fill the strokes between the sampled points with grayscale to obtain a grayscale image. Let p represent a certain pixel point in the grayscale image, and set the minimum pixel value G in the visualized grayscale image G min , and the maximum pixel value G max . Usually, for the convenience of clear observation by the human eye, in general, set G min to 30 - 50, and set G max = 255 as the maximum pixel value in an 8-bit grayscale image. Obtain the minimum non-zero grayscale value g min and the maximum grayscale value g max in the drawn grayscale image g. Among them,

[0071]

[0072] g min represents the minimum non-zero grayscale value in the grayscale image g, and g max represents the maximum grayscale value in the grayscale image g.

[0073] For the grayscale image obtained according to the filled grayscale value, call the formula:

[0074]

[0075] Calculate the visualized grayscale value G(p) of any point p in the grayscale image of the electronic signature handwriting, where g(p)≠0.

[0076] Save G(p) as a picture and then open it with a picture viewing software to observe.

[0077] So far, the echo process of the electronic signature containing timing information is completed. An example of the echoed electronic signature is shown in the appendix Figure 3 as shown, in the appendix Figure 3 On the left is the binary echo signature, and on the right is the echo of the electronic signature containing timing information. It can be seen that compared with the binary echo, the echo of the electronic signature containing timing information has a difference in the depth of the strokes. The lighter the stroke (gray), the earlier the writing time, and the darker the stroke (white), the later the writing time. Thus, the stroke order of the signature writing can be directly observed from the image. This is a feature that the binary echo does not have.

[0078] Furthermore, if it is necessary to improve the visualization quality of the echoed image, the grayscale image can be further mapped into an RGB image through methods such as a lookup table to improve the distinguishability between different pixel values by the human eye. The image contains mapped feature information, such as time information, pressure information, speed, angle, etc.

[0079] When scenarios such as comparison, identification, and recognition are required, through the grayscale image of the visual electronic signature trajectory or the mapped RGB image, the drawn grayscale image can be restored into a sequence through point position restoration. Taking mean filling or extreme value filling as an example, the method of restoring from an image to a sequence is introduced below.

[0080] In extreme value filling or mean filling, on the line segment between every two adjacent sampling points, the pixel values are the same, while the pixel values of different line segments are different. Therefore, first, traverse all the pixel values in the grayscale image, determine each line segment according to the grayscale value, and all line segments can be obtained; second, record the pixel coordinates of the endpoints of each line segment, and the positions of all sampling points of the electronic signature can be obtained; finally, sort according to the size of the pixel values corresponding to the positions of all sampling points, and the sequence of the electronic signature can be restored.

[0081] Furthermore, the image can be saved. In order to save the complete information of the grayscale image, when saving the image, a lossless image saving format needs to be adopted, such as PNG, BMP, etc.

[0082] As Figure 4 shown, the electronic device 300 includes a computing unit 301, which can execute various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 302 or the computer program loaded from the storage unit 308 into the random access memory (RAM) 303. In the RAM 303, various programs and data required for the operation of the device 300 can also be stored. The computing unit 301, the ROM 302, and the RAM 303 are connected to each other through a bus 304. The input / output (I / O) interface 305 is also connected to the bus 304.

[0083] Multiple components in the electronic device 300 are connected to the I / O interface 305, including: an input unit 306, an output unit 307, a storage unit 308, and a communication unit 309. The input unit 306 can be any type of device that can input information into the electronic device 300. The input unit 306 can receive input digital or character information, and generate key signal inputs related to the user settings and / or function controls of the electronic device. The output unit 307 can be any type of device that can present information, and can include but is not limited to a display, a speaker, a video / audio output terminal, a vibrator, and / or a printer. The storage unit 308 can include but is not limited to a magnetic disk, an optical disk. The communication unit 309 allows the electronic device 300 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks, and can include but is not limited to a modem, a network card, an infrared communication device, a wireless communication transceiver, and / or a chipset, such as a Bluetooth device, a WiFi device, a WiMax device, a cellular communication device, and / or the like.

[0084] The computing unit 301 can be various general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 301 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 301 executes the various methods and processes described above. For example, in some embodiments, the reconstruction and decomposition of the muscle movement trajectory redrawn from the original trajectory of the signature stroke, and the decomposition of its logarithmic velocity curve, etc. can be implemented as a computer software program, which is tangibly incorporated in a machine-readable medium, such as the storage unit 308. In some embodiments, part or all of the computer program can be loaded and / or installed onto the electronic device 300 via the ROM 302 and / or the communication unit 309. In some embodiments, the computing unit 301 can be configured to execute the signature handwriting dynamic acquisition implementation method by any other suitable means (e.g., by means of firmware).

[0085] The program code for implementing the methods of the present application can be written in any combination of one or more programming languages. These program codes can be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing devices, such that when the program codes are executed by the processor or controller, the functions / operations specified in the flowcharts and / or block diagrams are implemented. The program code can be executed entirely on the machine, partially on the machine, executed partially on the machine and partially on a remote machine as an independent software package, or executed entirely on a remote machine or server.

[0086] In the context of the present application, a machine-readable medium can be a tangible medium that can contain or store a program for use by or in connection with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0087] As used in this application, the terms "machine-readable medium" and "computer-readable medium" refer to any computer program product, apparatus, and / or device (e.g., magnetic disks, optical disks, memory, programmable logic devices (PLD)) used to provide machine instructions and / or data to a programmable processor, including a machine-readable medium that receives machine instructions as a machine-readable signal. The term "machine-readable signal" refers to any signal used to provide machine instructions and / or data to a programmable processor.

[0088] For purposes of providing an interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which the user can provide input to the computer. Other kinds of devices can also be used to provide for interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic, speech, or tactile input).

[0089] The systems and techniques described herein can be implemented in a computing system including a back-end component (e.g., as a data server), or a computing system including a middleware component (e.g., an application server), or a computing system including a front-end component (e.g., a user computer having a graphical user interface or a web browser through which the user can interact with an implementation of the systems and techniques described herein), or in a computing system including any combination of such back-end, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local area network (LAN), wide area network (WAN), and the Internet.

[0090] A computer system can include a client and a server. The client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other.

Claims

1. An electronic handwriting echo method including timing information, characterized in that, Real-time sampling of the electronic signature is performed to obtain a series of sampling point sequences containing signature timing feature information. The position information of each sampling point on the electronic signature trajectory is mapped to the gray value of the corresponding sampling point, and the line segment between adjacent sampling points is filled with the relevant gray value to draw the gray-scale image of the electronic signature; the visual electronic signature is obtained according to the gray-scale image.

2. The method according to claim 1, wherein Mapping the sampling points to gray values includes: assigning an initial gray value to the first sampling point in the sequence, and constructing a mapping relationship based on the current sampling point time t i , the initial time t0 when the signature starts to be written, and the initial gray value g(x0, y0): Calculate the grayscale value g(x i , y i ) of any point (x i , y i ) among the sampled points of the stroke trajectory.

3. The method according to claim 1, characterized in that The mapping of sampling points to gray values includes: presetting corresponding gray values for all possible time values t of the sampling points of the electronic signature, constructing a look-up table (LUT), and according to the position of the sampling points, according to the mapping relationship: g(x i ,y i ) = LUT(t i ) to obtain the gray values of each sampling point through the look-up table.

4. The method according to any one of claims 1-3, characterized in that, Interpolating to fill the gray value of the line segment between adjacent sampling points specifically includes: according to the gray value of the sampling point and the Euclidean distance between sampling points, calling the formula: Calculate the gray value g(p) of any point on the inserted connecting line segment, and draw the gray-scale signature trajectory diagram, where d(p, p i ), d(p i+1 , p i ) are the distances from any point on the filled stroke segment to the i-th sampling point and the adjacent sampling point, and g(p i+1 ), g(p i ) are the gray values of the adjacent sampling points.

5. The method according to any one of claims 1-3, characterized in that Using the extreme value to fill the gray value of the stroke segment between sampling points, and filling the gray value of all points on the connecting line segment between sampling points with the gray value of any one of the two adjacent sampling points to draw the gray-scale image of the signature trajectory.

6. The method according to any one of claims 1 to 3, characterized in that Using the gray mean value to fill the gray value of the stroke segment between sampling points, calculating the arithmetic mean of the gray values of adjacent sampling points as the gray value for filling the connecting stroke segment, and drawing the gray-scale image of the signature trajectory.

7. The method according to any one of claims 1 to 6, characterized in that Set the minimum pixel value \(G\) in the visualized grayscale image \(G\) min and the maximum pixel value \(G\) max , obtain the minimum non-zero grayscale value \(g\) in the drawn grayscale image min and the maximum grayscale value \(g\) max , call the formula: Calculating the visual gray value G(p) of any point p in the gray-scale image of the electronic signature handwriting, where g(p) is the gray value of point p obtained from the drawn gray-scale image, to obtain the visual gray-scale image of the electronic signature containing writing timing information.

8. The method according to any one of claims 1 to 6, characterized in that Furthermore, the gray-scale image is mapped into an RGB image through a look-up table to obtain an electronic signature trajectory image containing writing timing information; all pixel values in the gray-scale image are traversed, each line segment is determined according to the gray value, the pixel coordinates of the endpoints of each line segment are recorded, the positions of all sampling points of the electronic signature are obtained, and they are sorted according to the pixel value sizes corresponding to the positions where all sampling points are located to restore the sequence of the electronic signature.

9. An electronic device, comprising: A processor; And a memory storing a program, characterized in that the program includes instructions which, when executed by the processor, cause the processor to execute the electronic handwriting echo method containing writing information according to any one of claims 1-8.

10. A non-transitory computer-readable storage medium storing computer instructions, characterized in that, Wherein, The computer instructions are used to cause the computer to execute the electronic handwriting echo method containing writing information according to any one of claims 1-8.

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