Signature information acquisition device for signature electronization

Abstract

The embodiment of the invention provides a signature information acquisition device for signature electronization, and the device comprises an electronic signature input module which is used for receiving electronic signature data input by a first user, and the electronic signature data comprises a handwritten signature and an image signature; the storage module is used for storing handwriting feature parameters of a second user or three-dimensional contour data and texture detail data of the entity signature, and the second user is a user represented by the electronic signature; the electronic signature consistency determination module is used for determining the consistency with the characteristics represented by the electronic signature data according to the handwriting characteristic parameters of the second user or the three-dimensional contour data and the texture detail data of the entity signature; and the communication module is used for transmitting the electronic signature data to the target equipment after the signature passes the consistency comparison. According to the invention, the security of signature electronization can be improved.

Description

Technical Field

[0001] The present invention belongs to the field of information security technology, and in particular relates to a signature information collection device for electronic signature. Background Art

[0002] In business activities and various document signing scenarios, signatures have always played a key role as an important means to confirm the validity of documents and clarify the responsibility. The traditional way of signing mainly relies on physical seals and handwritten signatures. With the rapid development of digital technology, this traditional method can no longer keep up with the pace of development. Therefore, various industries are actively promoting digital transformation to improve work efficiency, reduce costs, and enhance competitiveness.

[0003] In this context, electronic signatures have become an inevitable trend. It can convert traditional physical signatures and handwritten signatures into digital forms and realize online signing and management. However, the current electronic signature process faces security problems. At present, electronic signatures also face severe challenges in terms of security. The electronic signature process does not provide sufficient information for subsequent security verification, which increases the risk of forged electronic signatures. Summary of the invention

[0004] In view of this, an object of the present invention is to provide a signature information collection device for electronic signature to meet the demand for improving the security of electronic signature.

[0005] In order to achieve the above object, the present invention provides the following technical solutions: The present invention provides a signature information collection device for electronic signature, comprising: an electronic signature input module, used for receiving electronic signature data input by a first user, the electronic signature data including a handwritten signature and an imaged signature; a storage module, used for storing handwriting feature parameters of a second user or three-dimensional contour data and texture detail data of a physical signature, the second user being the user represented by the electronic signature; an electronic signature consistency determination module, used for determining consistency with features represented by the electronic signature data based on the handwriting feature parameters of the second user or the three-dimensional contour data and texture detail data of the physical signature; and a communication module, used for transmitting the electronic signature data to a target device after the signature passes the consistency comparison.

[0006] Optionally, a signature information collection device for electronic signature also includes: a biometric information collection module, used to collect the biometric information of the first user for entering electronic signature data; a first encryption module, used to encrypt and encode the electronic signature data and the first user's biometric data to obtain target electronic signature data; wherein the communication module is used to transmit the target electronic signature data to the target device when the signature passes the consistency comparison.

[0007] Optionally, the electronic signature entry module includes: an automatic fill light module, used to automatically fill light to the scanning area according to the current light; a scanning module, used to scan the scanning area to obtain a signature image; and an automatic distortion correction module, used to automatically correct the signature image.

[0008] Optionally, a signature information collection device for electronic signature, an electronic signature entry module, includes: an electronic signature module, used to receive the user's handwritten signature data; a pressure sensor array, used to collect the pressure of different areas when the user's handwritten signature is generated; a timer, connected to the pressure sensor array, used to record the time when pressure is generated in different areas when the user's handwritten signature is generated; a second encryption module, used to extract handwriting feature parameters based on the pressure sensor array and timer data when the user's handwritten signature data is generated, pre-process the handwriting feature parameters, and then asymmetrically encrypt the handwritten signature data based on the pre-processed handwriting feature parameters to obtain an encrypted user electronic signature.

[0009] Optionally, the electronic signature is converted from a physical seal, and the consistency of the features represented by the electronic signature data is determined based on the three-dimensional contour data and texture detail data of the physical signature, including: constructing a three-dimensional digital model of the signature based on the three-dimensional contour data and texture detail data of the physical signature; determining multiple target projection angles based on the geometric characteristics of the three-dimensional digital model of the signature; projecting the signature part of the three-dimensional digital model of the signature onto a two-dimensional plane at multiple target projection angles according to the projection algorithm of computer graphics to obtain multiple two-dimensional projections; performing feature pooling on the multiple two-dimensional projections, and performing feature fusion on the multiple two-dimensional projections to obtain the three-dimensional signature. Fusion features of the signature part in the digital model; extracting multiple types of feature data from the electronic signature according to the target feature extraction algorithm, including contour features and texture semantic features; determining contour features in the fused features, and determining the consistency between the contour features in the electronic signature and the contour features in the corresponding fused features according to the first target algorithm; determining texture semantic features in the fused features, and determining the consistency between the texture semantic features in the electronic signature and the texture semantic features in the corresponding fused features according to the second target algorithm; determining the consistency between the physical signature and the electronic signature features based on the consistency between the contour features and the consistency between the texture semantic features.

[0010] Optionally, the electronic signature is an encrypted user electronic signature, and the handwriting feature parameters are preprocessed, including: querying the mapping table for the set of numerical ranges where each handwriting feature parameter is located, and using each numerical range set number as the preprocessed handwriting feature parameter; based on the handwriting feature parameters of the second user, determining the consistency with the features represented by the electronic signature data, including: querying the mapping table for the set of numerical ranges where the handwriting feature parameters of the second user are located, using each numerical range set number as a decryption key element, and using an asymmetric decryption method for decryption; when the decryption is successful, it indicates that the features represented by the electronic signature data are consistent with the handwriting feature parameters of the second user; when the decryption is unsuccessful, it indicates that the features represented by the electronic signature data are inconsistent with the handwriting feature parameters of the second user.

[0011] Optionally, a signature information collection device for electronic signature further includes: when the characteristics represented by the electronic signature data are consistent with the handwriting feature parameters of the second user, the second user number is added to the electronic signature data, and the electronic signature data with the second user number added is sent to the target device.

[0012] Optionally, a signature information collection device for electronic signature further includes: a saddle signature recognition module, used to identify whether the electronic signature data entered by the first user is a saddle signature; and a saddle signature optimization module, used to optimize the saddle signature image when it is identified as a saddle signature.

[0013] Optionally, a signature information collection device for electronic signature further includes: an electromagnetic shielding structure, arranged on the outer surface of the main body of the signature information collection device for electronic signature, including alternating conductive layers and magnetic conductive layers, for blocking or attenuating external electromagnetic waves.

[0014] The embodiment of the present invention provides a signature information collection device for electronic signature. In terms of data collection, it ensures comprehensive and accurate collection of signature features, laying a solid foundation for subsequent security verification. In terms of data processing and verification, it can determine the authenticity of the entered signature by judging the consistency between the entered signature and the pre-stored valid signature, plugging loopholes and preventing lawbreakers from signing on behalf of others or forging signatures for electronicization. In terms of data storage and transmission, a safe and reliable encryption verification mechanism is used to protect electronic signature data from being tampered with, prevent data from being intercepted and destroyed by middlemen during transmission, and improve the security of electronic signatures.

[0015] Other advantages, objectives and features of the present invention will be described in the following description and will be apparent to those skilled in the art to some extent, or those skilled in the art may be taught from the practice of the present invention. The objectives and other advantages of the present invention may be realized and obtained through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to make the purpose, technical solution and beneficial effects of the present invention clearer, the present invention provides the following drawings for illustration: Figure 1 This is a schematic diagram of the module composition of a signature information collection device for electronic signature in an embodiment of the present invention; Figure 2 The figure is a flow chart of a method for determining consistency of features in an embodiment of the present invention. DETAILED DESCRIPTION

[0017] The technical solution of the present invention will be described clearly and completely below in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0018] In the description of the present invention, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, it can also be the internal connection of two components, it can be a wireless connection, or it can be a wired connection. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0019] In addition, the technical features involved in the different embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0020] The embodiment of the present invention provides a signature information collection device for electronic signature, such as Figure 1 As shown, including: The electronic signature input module 101 is used to receive the electronic signature data input by the first user, where the electronic signature data includes a handwritten signature and an image signature; Storage module 102, used to store handwriting feature parameters of a second user or three-dimensional contour data and texture detail data of a physical signature, where the second user is the user represented by the electronic signature; The electronic signature consistency determination module 103 is used to determine the consistency with the features represented by the electronic signature data based on the handwriting feature parameters of the second user or the three-dimensional contour data and texture detail data of the physical signature; The communication module 104 is used to transmit the electronic signature data to the target device after the signature passes the consistency comparison.

[0021] Exemplarily, the electronic signature input module 101 may be an electronic signature board, an image acquisition device, etc., wherein the image acquisition device may be a camera or a scanning device, which is not limited in this embodiment. The electronic signature data input by the first user may be a handwritten signature or an imaged signature, such as a stamped image on a paper document.

[0022] The storage module 102 may be a memory stick or other device with storage function. The storage module 102 receives in advance the second user's handwriting feature parameters or the three-dimensional contour data and texture detail data of the physical seal imported by the external device, wherein the handwriting feature parameters include stroke feature parameters, writing speed parameters, pressure feature parameters, etc. The stroke feature parameters may include stroke width and stroke inclination angle, etc. The three-dimensional contour data of the physical seal includes shape data, edge contour data, and concave-convex feature data, etc. Among them, the shape data includes shape parameters and size parameters. When the shape is a circle, the size parameter is the radius length, when the shape is a quadrilateral, the size parameter is the side length, when the shape is an ellipse, the size parameter is the major and minor axis length, and when the shape is a polygon, the size parameter is the length of each side length and the corresponding angle. The edge contour data includes edge curve coordinates and / or edge roughness data, and the concave-convex feature data includes convex part data and concave part data. The external device may be a computing device with handwriting input function and handwriting feature parameter analysis, or may be a computing device with image scanning or image acquisition and image data processing. It should be noted that the second user and the first user may be the same user or different users, which is not limited in this embodiment.

[0023] The electronic signature consistency determination module 103 may be a computing module with an image recognition algorithm and a consistency comparison algorithm. The image recognition algorithm may identify the user name represented by the signature text or the signature, thereby retrieving the corresponding three-dimensional contour data of the physical signature and the texture detail data or the handwriting feature parameters corresponding to the user name from the memory. The consistency comparison algorithm may compare the contour data of the extracted electronic signature imaged signature with the stored three-dimensional contour data of the physical signature. For example, a shape matching algorithm, such as a shape matching method based on Fourier descriptors, may be used to calculate the similarity of the contours of the two. For texture detail data, a texture analysis algorithm, such as a gray level co-occurrence matrix (GLCM) algorithm, is used to calculate the similarity of texture features, and to compare whether the texture direction, frequency and other features are consistent. The results of the contour similarity and texture similarity are combined to form an overall consistency judgment index. A comprehensive threshold may be set. When both the contour similarity and the texture similarity reach a certain level, and the comprehensive index exceeds the threshold, it is considered that the electronic signature data is consistent with the three-dimensional contour data and texture detail data of the physical signature. For the comparison of handwriting feature parameters, the preprocessed electronic signature handwriting feature parameters are matched one by one with the handwriting feature parameters of the second user in the storage module. For example, compare whether the stroke lengths are equal within a certain error range, and whether the deviation of the stroke angles is within an acceptable threshold. For dynamic features such as writing speed and pressure changes, algorithms such as dynamic time warping are used to calculate the similarity between the two to adapt to situations where the writing speeds are different but the features are similar. This embodiment does not limit the consistency comparison algorithm, and those skilled in the art can determine it as needed.

[0024] The communication module 104 is used to transmit the electronic signature data to the target device after the signature passes the consistency comparison. The target device may be a computer, a storage device, etc. When the signature fails to pass the consistency comparison, an alarm may be issued, and the electronic signature data will not be uploaded to the target device. It should be noted that in order to ensure that the electronic signature information collection device is the only device for the target device to obtain the electronic signature information, a firewall whitelist may be set on the target device to allow only the device to upload data, thereby ensuring that all electronic signatures in the target device are authentic and secure.

[0025] The embodiment of the present invention provides a signature information collection device for electronic signature. In terms of data collection, it ensures comprehensive and accurate collection of signature features, laying a solid foundation for subsequent security verification. In terms of data processing and verification, it can determine the authenticity of the entered signature by judging the consistency between the entered signature and the pre-stored valid signature, plugging loopholes and preventing lawbreakers from signing on behalf of others or forging signatures for electronicization. In terms of data storage and transmission, a safe and reliable encryption verification mechanism is used to protect electronic signature data from being tampered with, prevent data from being intercepted and destroyed by middlemen during transmission, and improve the security of electronic signatures.

[0026] As an optional implementation, a signature information collection device for electronic signature further includes: The biometric information collection module is used to collect the biometric information of the first user for entering the electronic signature data; the first encryption module is used to encrypt and encode the electronic signature data and the first user's biometric data to obtain the target electronic signature data; wherein the communication module is used to transmit the target electronic signature data to the target device when the signature passes the consistency comparison.

[0027] Exemplarily, the biometric information collection module includes a fingerprint recognition device, a facial recognition camera, an iris recognition device, etc. It should be noted that in this embodiment, all biometric information collection processes are carried out after a clear prompt message has been sent to the user to inform the user that biometric collection is required and the consent is obtained. The first encryption module is a computing module that stores an encryption algorithm and a random number generator. The module associates and integrates the electronic signature data and the biometric information data to form a data set to be encrypted, ensuring that the corresponding relationship between the two is clear, so that subsequent encryption operations can simultaneously protect the security of the two parts of data. The encryption algorithm can be an advanced encryption standard (AES), elliptic curve encryption (ECC) or RSA algorithm, etc. A pair or a group of keys is generated using the key generation mechanism of the encryption algorithm. The key generation process usually relies on a secure random number generator to ensure the randomness and unpredictability of the key. For symmetric encryption algorithms (such as AES), a shared key is generated; for asymmetric encryption algorithms (such as RSA, ECC), a public key and a private key pair are generated. Based on the biometric information collection module and encryption module proposed in this embodiment, the electronic signature data transmitted to the target device in this embodiment is the target electronic signature data obtained by encrypting the electronic signature data and the first user's biometric data. The security of the data is ensured by encryption, and the traceability of the use of the electronic signature can be improved by collecting the first user's biometric data.

[0028] As an optional implementation, a signature information collection device for electronic signature, an electronic signature input module, includes: Automatic fill light module, used to automatically fill light to the scanning area according to the current light; A scanning module is used to scan the scanning area to obtain a signature image; The automatic distortion correction module is used to automatically correct the signature image.

[0029] Exemplarily, the automatic fill light module includes a light sensor and a control module. The light sensor is used to detect the intensity of the current ambient light in real time and transmit the detected light intensity value (usually in Lux) to the control module. The control module calculates whether the current ambient light meets the scanning requirements based on the data transmitted by the light sensor. If the light is insufficient, the control module calculates the light intensity that needs to be supplemented based on the preset light threshold. For example, if the preset minimum light threshold is 350 Lux, and the currently detected light intensity is 200 Lux, 150 Lux of light needs to be supplemented. The control module automatically adjusts the brightness of the fill light according to the calculation result. The fill light can be an LED lamp, and the brightness is controlled by adjusting the current or PWM (pulse width modulation) signal. The light direction and angle of the fill light can also be adjusted as needed to ensure that the light is evenly irradiated on the scanning area. After the fill light, the light sensor detects the light intensity of the scanning area again to ensure that the light is uniform and reaches the preset threshold. If the light still does not meet the requirements, the control module continues to adjust the brightness of the fill light until the light reaches the ideal state.

[0030] When the automatic fill light module reaches the ideal state, the scanning module starts scanning to obtain the signature image. After scanning, the acquired image can also be pre-processed, such as denoising, contrast adjustment, etc., to improve the image quality. Then, the automatic distortion correction module obtains the scanned signature image data from the scanning module. Use image processing algorithms (such as edge detection, corner point detection, etc.) to detect the distortion in the image. For example, by detecting the edge straight line of the image, it is determined whether there is perspective distortion or geometric distortion. According to the type and degree of distortion detected, a suitable correction algorithm is selected, such as perspective correction, geometric distortion correction, etc. The correction algorithm is applied to process the image to obtain a corrected image. Finally, the quality of the corrected image is evaluated to check whether there is residual distortion or distortion. If the image quality is not ideal, the parameters of the correction algorithm can be adjusted and re-corrected until the image quality meets the requirements. The embodiment of the present invention provides a signature information collection device for electronic signature, which can improve the effect of electronic signature entry and the accuracy of subsequent comparison through the automatic fill light module and the automatic distortion correction module.

[0031] As an optional implementation, the electronic signature entry module includes: Electronic signature module, used to receive the user's handwritten signature data; The pressure sensor array is used to collect the pressure of different areas when the user writes a signature; A timer, connected to the pressure sensor array, for recording the time when pressure is generated in different areas when the user writes a signature; The second encryption module is used to extract handwriting feature parameters from the pressure sensor array and timer data when the user writes the handwriting signature data, pre-process the handwriting feature parameters, and then asymmetrically encrypt the handwritten signature data according to the pre-processed handwriting feature parameters to obtain an encrypted user electronic signature.

[0032] Exemplarily, the electronic signature module can be an electronic version with only a handwritten signature function, such as a handwriting tablet, or a mobile device with a touch screen (such as a tablet or a smart phone). A pressure sensor array is integrated under the handwriting tablet or touch screen to detect the pressure distribution during signing in real time. The pressure sensor array converts the detected pressure data into an electrical signal and transmits it to the processing module through an interface. The processing module synchronizes the pressure data with the signature image and records the pressure changes of each stroke. The timer is connected to the pressure sensor array, and a high-precision timer is used to record the start and end time of each stroke during the signing process. The timer and the pressure sensor array work synchronously to ensure that the time data corresponds to the pressure data one by one. Finally, the time data and the pressure data are combined to form complete dynamic feature data of the handwritten signature.

[0033] The second encryption module extracts handwriting feature parameters such as stroke feature parameters, writing speed parameters, pressure feature parameters, etc. from the pressure sensor array and timer data when the user writes the handwritten signature data, pre-processes the handwriting feature parameters, and then asymmetrically encrypts the handwritten signature data according to the pre-processed handwriting feature parameters to obtain an encrypted user electronic signature. This embodiment uses the pre-processed handwriting feature parameters to asymmetrically encrypt the handwritten signature data in order to subsequently use the pre-stored second user handwriting feature parameters to decrypt it, and judge whether the decryption can be completed to determine whether the handwritten signature data has the signature entry authorization, or whether it is a proxy signature. The specific decryption method can be to call all the second user handwriting feature parameters that have been stored in the storage module, and decrypt these second user handwriting feature parameters in turn as the decryption key elements of the asymmetric decryption algorithm. If the decryption is successful, it is considered that the entered handwritten signature meets the entry authorization conditions.

[0034] Furthermore, since there is also the behavior of signing on behalf of others, for example, both user A and user B have the authorization to enter handwritten signatures, and user A signs the name of user B and enters it into the device. In this case, since the handwriting feature parameters of user A can match the user handwriting feature parameters stored in the storage module, this kind of signing on behalf of others may not be identified. Therefore, the decrypted user handwritten signature can also be used for name recognition to obtain the signed user name, and the signed user name is compared with the user name corresponding to the decrypted second user handwriting feature parameters to determine whether it is a signing on behalf of others.

[0035] As an optional implementation, the electronic signature is converted from a physical seal, and the consistency of the features represented by the electronic signature data is determined based on the three-dimensional contour data and texture detail data of the physical seal, such as Figure 2 As shown, it includes: S101, constructing a three-dimensional signature digital model according to the three-dimensional contour data and texture detail data of the physical signature; S102, determining multiple target projection angles based on the geometric characteristics of the three-dimensional signature digital model; S103, projecting the signature part of the three-dimensional signature digital model onto a two-dimensional plane at multiple target projection angles according to a projection algorithm of computer graphics to obtain multiple two-dimensional projections; S104, performing feature pooling on the multiple two-dimensional projections, and performing feature fusion on the multiple two-dimensional projections to obtain fusion features of the signature part in the three-dimensional signature digital model; S105, extracting multiple types of feature data from the electronic signature according to a target feature extraction algorithm, including contour features and texture semantic features; S106, determining contour features in the fused features, and determining consistency between the contour features in the electronic signature and the contour features in the corresponding fused features according to the first target algorithm; S107, determining a texture semantic feature in the fused feature, and determining the consistency between the texture semantic feature in the electronic signature and the texture semantic feature in the corresponding fused feature according to the second target algorithm; S108, determining the consistency between the physical signature and the electronic signature features based on the consistency between the contour features and the consistency between the texture semantic features.

[0036] Exemplarily, first, the collected three-dimensional contour data is denoised to remove noise points caused by scanning errors, and a filtering algorithm is used to smooth the data. For texture detail photos, grayscale, contrast enhancement and other operations are performed to improve the clarity of texture information. Then, a three-dimensional modeling software is used to import the pre-processed three-dimensional contour data and texture detail data, and a three-dimensional model is constructed in the software based on the actual shape and size of the physical signature, and the texture is mapped to the model surface. Then, the geometric characteristics of the constructed three-dimensional signature digital model are analyzed to determine the key geometric elements of the model, such as the axis of symmetry and the main plane. For example, for a square seal, the plane where the four sides and diagonals are located is the key analysis object. Therefore, the projection angle can be calculated by a mathematical algorithm based on the geometric characteristics and the center of the model as the reference point. Specifically, the projection can be based on the principle of uniform distribution and multiple equally spaced points selected within a certain range. For a square seal, the points corresponding to the midpoints of the four sides of the square seal can be vertically extended to a position 20 cm away, and a depression angle of 30° can be used as four projection angles to ensure that the projection information of the model is obtained from multiple directions. For a circular seal, the point can be determined by dividing the circumference into six parts, and then vertically extending from the point, with a depression angle of 30° as the six projection angles. This embodiment does not limit the method for determining the projection angle, and technical personnel in this field can determine it as needed.

[0037] The orthogonal projection algorithm in computer graphics is used to input the signature part of the three-dimensional signature digital model into the projection algorithm for calculation under multiple selected target projection angles. The calculation result is rendered on a two-dimensional plane to generate a two-dimensional projection image. The multiple two-dimensional projection images are the seal parts in the three-dimensional signature digital model mapped from multiple angles. In this way, in the subsequent comparison, it can adapt to the situation that the first user actually stamps the signature on the paper from different force directions due to the environment and personal habits, so that the seal mark is distorted. This embodiment maps the seal part in the three-dimensional signature digital model from multiple angles, and compares the seal features of the three-dimensional signature digital model that integrates the mapping of multiple angles with the electronic signature data entered by the first user for consistency. It can avoid the situation that the electronic signature data entered by the first user is distorted due to personal force habits or environmental factors, and cannot be matched with the two-dimensional projection of the three-dimensional signature digital model mapped at a fixed angle, thereby reducing the matching accuracy.

[0038] For multiple two-dimensional projection images, the maximum pooling or average pooling method is used. Maximum pooling selects the maximum value in the pooling area as the output feature to highlight the key features in the image; average pooling calculates the average value in the pooling area as the output feature, which can smooth the image features. The multiple two-dimensional projection feature maps after pooling are fused. Specifically, the channel splicing method can be used to connect different feature maps in the channel dimension to form a fused feature tensor. The weighted fusion method can also be used to assign different weights according to the importance of each two-dimensional projection, and then the weighted feature maps are added to obtain the fused feature.

[0039] The target feature extraction algorithm includes edge detection algorithms, such as the Canny algorithm, the Sobel algorithm, etc. Taking the Canny algorithm as an example, the electronic signature image is first subjected to Gaussian filtering for noise reduction, then the gradient amplitude and direction of the image are calculated, the edge is refined by non-maximum suppression, and finally the image contour is determined by dual threshold detection and edge tracking, and the contour features and texture semantic features are extracted.

[0040] After extracting the contour features and texture semantic features, the first target algorithm and the second target algorithm are used to calculate the consistency of the texture semantic features in the electronic signature and the corresponding fusion features. Specifically, the first target algorithm can use a shape matching algorithm, such as a matching algorithm based on Fourier descriptors. The Fourier descriptor of the contour features extracted from the electronic signature is compared with the Fourier descriptor of the contour features in the fusion features, and the similarity between the two is calculated. A similarity threshold is set. If the similarity is higher than the threshold, the contour features of the two are considered to be consistent; otherwise, they are inconsistent. The second target algorithm can use a cosine similarity algorithm. The texture semantic feature vector extracted from the electronic signature and the texture semantic feature vector in the fusion features are normalized, and then their cosine similarity is calculated. A threshold is also set, and the consistency of the texture semantic features is determined based on the comparison result of the similarity and the threshold. This embodiment does not limit the first target algorithm and the second target algorithm, and those skilled in the art can determine it as needed.

[0041] As an optional implementation, the electronic signature is an encrypted user electronic signature, and the handwriting feature parameters are preprocessed, including: searching the mapping table for a set of numerical ranges where each handwriting feature parameter is located, and using each numerical range set number as the preprocessed handwriting feature parameter; Based on the handwriting feature parameters of the second user, the consistency with the features represented by the electronic signature data is determined, including: querying the numerical range set where the handwriting feature parameters of the second user are located in the mapping table, using each numerical range set number as a decryption key element, and using an asymmetric decryption method to decrypt; when the decryption is successful, it means that the features represented by the electronic signature data are consistent with the handwriting feature parameters of the second user; when the decryption is unsuccessful, it means that the features represented by the electronic signature data are inconsistent with the handwriting feature parameters of the second user.

[0042] Exemplarily, in order to prevent the handwriting feature parameters of the first user from being different due to changes in the environment or personal status, which may result in the inability to match the handwriting feature parameters of the second user in the storage module, in this embodiment, the handwriting feature parameters are preprocessed before the encryption process is performed in the second encryption module. The specific method is to expand the range of the handwriting feature parameters. Taking the handwriting feature parameters as stroke feature parameters as an example, the set in which the stroke inclination angle is located is queried, and the set number is used as the stroke inclination angle value. For example, a stroke inclination angle is 15°, which is included in the set of 14°-16°, and the set number is 10. Then the number 10 can be used as the stroke inclination angle value. It should be noted that in this case, the handwriting feature parameters of the second user stored in the storage module are also obtained in the same way.

[0043] After preprocessing the handwriting feature parameters in the above manner, the second encryption module is used to asymmetrically encrypt the handwriting signature data using the preprocessed handwriting feature parameters as encryption key elements to obtain an encrypted user electronic signature. On this basis, this embodiment uses the numerical range number corresponding to the second user's handwriting feature parameters in the storage module as a decryption key element, and uses an asymmetric decryption method for decryption. If decryption is successful, it means that the features represented by the electronic signature data are consistent with the handwriting feature parameters of the second user; if decryption is unsuccessful, it means that the features represented by the electronic signature data are inconsistent with the handwriting feature parameters of the second user. It should be noted that the order of the handwriting feature parameter numbers in the encryption process and the order of the handwriting feature parameter numbers in the decryption process are pre-agreed.

[0044] As an optional implementation, a signature information collection device for electronic signature also includes: when the characteristics represented by the electronic signature data are consistent with the handwriting feature parameters of the second user, the second user number is added to the electronic signature data, and the electronic signature data with the second user number added is sent to the target device. The second user number is used to represent the identity of the second user. By synchronously sending the second user number to the target device, the signing user can be effectively traced.

[0045] As an optional implementation, a signature information collection device for electronic signature further includes: A saddle signature recognition module, used to recognize whether the electronic signature data entered by the first user is a saddle signature; The saddle signature optimization module is used to optimize the saddle signature image when it is identified as a saddle signature.

[0046] Exemplarily, before recognition, the electronic signature data entered by the first user is first preprocessed. Through the grayscale operation, the color image is converted into a grayscale image to simplify subsequent calculations, and the noise interference in the image is removed by the noise reduction algorithm to improve the image quality. The image enhancement technology is used to enhance the contrast of the image and highlight the signature details. Then, feature extraction is performed. Since the edges of the saddle signature usually have unique continuity and break features, the edge detection algorithm is used to extract the edge information of the image. Finally, based on the extracted features, machine learning or deep learning models are used for recognition. In terms of machine learning, a support vector machine (SVM) model can be trained, and the extracted features are used as input. The SVM is trained with a large number of labeled saddle signature and non-saddle signature samples to learn the feature differences between the two, thereby achieving classification and recognition. In terms of deep learning, a convolutional neural network (CNN) model is constructed, and CNN is used to automatically extract deep features of the image, such as using classic network structures such as VGG and ResNet, and training with a large amount of image data to enable it to accurately determine whether the image is a saddle signature. After the saddle seal is identified, the image repair algorithm is used to repair the broken or blurred areas where the saddle seal crosses the gap between the papers. For example, the repair method based on partial differential equations analyzes the pixel information around the broken area and fills and repairs the broken area according to a certain mathematical model to make the lines of the signature continuous and complete.

[0047] As an optional implementation, a signature information collection device for electronic signature further includes: The electromagnetic shielding structure is arranged on the outer surface of the main body of the signature information collection device for electronic signature, including alternating conductive layers and magnetic conductive layers, which are used to block or attenuate external electromagnetic waves.

[0048] Finally, it should be noted that the above preferred embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail through the above preferred embodiments, those skilled in the art should understand that various changes can be made in form and details without departing from the scope defined by the claims of the present invention.

Claims

1. A signature information collection device for electronic signature, characterized in that: include: An electronic signature input module, used to receive electronic signature data input by a first user, where the electronic signature data includes a handwritten signature and an image signature; A storage module, used to store handwriting feature parameters of a second user or three-dimensional contour data and texture detail data of a physical signature, where the second user is the user represented by the electronic signature; An electronic signature consistency determination module, used to determine the consistency with the features represented by the electronic signature data based on the handwriting feature parameters of the second user or the three-dimensional contour data and texture detail data of the physical signature; The communication module is used to transmit the electronic signature data to the target device after the signature passes the consistency comparison.

2. A signature information collection device for electronic signature according to claim 1, characterized in that: Also includes: A biometric information collection module, used to collect the biometric information of the first user who enters the electronic signature data; A first encryption module, used to encrypt and encode the electronic signature data and the first user's biometric data to obtain target electronic signature data; Among them, the communication module is used to transmit the target electronic signature data to the target device when the signature passes the consistency comparison.

3. The signature information collection device for electronic signature according to claim 1, characterized in that: Electronic signature entry module, including: Automatic fill light module, used to automatically fill light to the scanning area according to the current light; A scanning module is used to scan the scanning area to obtain a signature image; The automatic distortion correction module is used to automatically correct the signature image.

4. The signature information collection device for electronic signature according to claim 1, characterized in that: Electronic signature entry module, including: Electronic signature module, used to receive the user's handwritten signature data; The pressure sensor array is used to collect the pressure of different areas when the user writes a signature; A timer, connected to the pressure sensor array, for recording the time when pressure is generated in different areas when the user writes a signature; The second encryption module is used to extract handwriting feature parameters from the pressure sensor array and timer data when the user writes the handwriting signature data, pre-process the handwriting feature parameters, and then asymmetrically encrypt the handwritten signature data according to the pre-processed handwriting feature parameters to obtain an encrypted user electronic signature.

5. The signature information collection device for electronic signature according to claim 3, characterized in that: The electronic signature is converted from the physical seal. Based on the three-dimensional contour data and texture detail data of the physical seal, the consistency of the features represented by the electronic signature data is determined, including: Construct a three-dimensional digital model of the signature based on the three-dimensional contour data and texture detail data of the physical signature; Based on the geometric characteristics of the three-dimensional signature digital model, multiple target projection angles are determined; According to the projection algorithm of computer graphics, the signature part of the three-dimensional signature digital model is projected onto a two-dimensional plane at multiple target projection angles to obtain multiple two-dimensional projections; Perform feature pooling on multiple two-dimensional projections, perform feature fusion on multiple two-dimensional projections, and obtain the fusion features of the signature part in the three-dimensional signature digital model; According to the target feature extraction algorithm, multiple types of feature data are extracted from the electronic signature, including contour features and texture semantic features; Determine the contour feature in the fused feature, and determine the consistency between the contour feature in the electronic signature and the contour feature in the corresponding fused feature according to the first target algorithm; Determine the texture semantic features in the fused features, and determine the consistency between the texture semantic features in the electronic signature and the texture semantic features in the corresponding fused features according to the second target algorithm; The consistency between the physical signature and the electronic signature features is determined based on the consistency between the contour features and the consistency between the texture semantic features.

6. The signature information collection device for electronic signature according to claim 4, characterized in that: The electronic signature is an encrypted user electronic signature, which pre-processes the handwriting feature parameters, including: Query the value range set of each handwriting feature parameter in the mapping table, and use the number of each value range set as the preprocessed handwriting feature parameter; Determining the consistency of the handwriting feature parameters of the second user with the features represented by the electronic signature data includes: Query the mapping table for the set of numerical ranges where the handwriting feature parameters of the second user are located, use the number of each numerical range set as a decryption key element, and use an asymmetric decryption method to decrypt. If the decryption is successful, it means that the features represented by the electronic signature data are consistent with the handwriting feature parameters of the second user; When the decryption fails, it means that the characteristics represented by the electronic signature data are inconsistent with the handwriting characteristic parameters of the second user.

7. The signature information collection device for electronic signature according to claim 6, characterized in that: Also includes: When the feature represented by the electronic signature data is consistent with the handwriting feature parameter of the second user, the second user number is added to the electronic signature data, and the electronic signature data with the second user number added is sent to the target device.

8. The signature information collection device for electronic signature according to claim 1, characterized in that: Also includes: A saddle signature recognition module, used to recognize whether the electronic signature data entered by the first user is a saddle signature; The saddle signature optimization module is used to optimize the saddle signature image when it is identified as a saddle signature.

9. The signature information collection device for electronic signature according to claim 1, characterized in that: Also includes: The electromagnetic shielding structure is arranged on the outer surface of the main body of the signature information collection device for electronic signature, including alternating conductive layers and magnetic conductive layers, which are used to block or attenuate external electromagnetic waves.

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