Signature verification system and signature verification method based on image analysis

Abstract

A signature verification system and method based on image analysis, the signature verification method based on image analysis comprising: collecting a handwriting data of a signer during a signature process by a signature collecting device; collecting an image data of the signer during the signature process by an image collecting device; obtaining at least one feature information from the image data; comparing the handwriting data and the at least one feature information with at least one authentication reference data to generate a comparison result; and judging authenticity of the signature process of the signer according to the comparison result.

Description

Technical Field

[0001] This invention relates to a signature verification system and method based on image analysis, and particularly to a signature verification system and method that uses an image acquisition device to acquire image data during the signing process and uses this data to determine the authenticity of the signature. Background Technology

[0002] Traditional signature verification methods primarily rely on static signature comparison. For example, when signing a document, verifiers typically need to visually compare the current signature with a pre-stored signature template. This comparison method relies purely on the verifier's experience and judgment, which is prone to subjective errors. Furthermore, static signature comparison cannot reflect the dynamic characteristics of the signing process, such as the speed and force of the signing, making it easily susceptible to forgery.

[0003] With the development of technology, the application of electronic signature pads is becoming increasingly widespread. However, electronic signature pads can only record signature information on a two-dimensional plane, and still lack verification of the signature process characteristics, making it difficult to effectively prevent imitation by others. As for the development of biometric recognition technologies (such as fingerprint recognition, facial recognition, iris recognition, etc.), although they have provided new solutions for identity verification, they usually require additional or special hardware support and cannot be effectively integrated with the signature verification process.

[0004] In view of this, providing a more reliable signature verification mechanism without the need for special hardware has become one of the goals that the industry is striving for. Summary of the Invention

[0005] Therefore, the main objective of this invention is to provide a signature verification system and method based on image analysis, so as to provide a more reliable signature verification mechanism.

[0006] This invention discloses a signature verification method based on image analysis, comprising: acquiring handwriting data of a signer during a signature process using a signature acquisition device; acquiring image data of the signer during the signature process using an image acquisition device; obtaining at least one feature information from the image data; comparing the handwriting data and the at least one feature information with at least one authentication reference data to generate a comparison result; and determining the authenticity of the signer's signature process based on the comparison result.

[0007] This invention also discloses an image analysis-based signature verification system, comprising a signature acquisition device for acquiring handwriting; an image acquisition device for acquiring images; a processing unit coupled to the signature acquisition device and the image acquisition device; and a storage unit coupled to the processing unit and storing an application program that instructs the processing unit to execute a signature verification method. The signature verification method includes the following steps: acquiring handwriting data of a signer during a signature process using the signature acquisition device; acquiring image data of the signer during the signature process using the image acquisition device; obtaining at least one feature information from the image data; comparing the handwriting data and the at least one feature information with at least one authentication reference data to generate a comparison result; and determining the authenticity of the signer's signature process based on the comparison result. Attached Figure Description

[0008] Figure 1 This is a schematic diagram of the signature verification system according to Embodiment 1 of the present invention.

[0009] Figure 2 This is a schematic diagram of the signature verification process according to Embodiment 1 of the present invention.

[0010] Figure 3A , Figure 3B , Figure 3C and Figure 3D This is a diagram illustrating the signing process.

[0011] In the picture: 10: Signature Verification System 100: Image acquisition device 101: Signature Collection Device 102: Processing Unit 104: Storage Unit 106: Application 20: Signature Verification Process 200-210: Steps A: Knuckles RT: Trajectory L1~L5: Distance C1~C4: Texture pattern. Detailed Implementation

[0012] The present invention will be further described below with reference to the accompanying drawings and specific embodiments, so that those skilled in the art can better understand and implement the present invention. However, the embodiments described are not intended to limit the present invention. Please refer to... Figure 1 , Figure 1This is a schematic diagram of a signature verification system 10 according to an embodiment of the present invention. The signature verification system 10 verifies the authenticity of a signer's signature based on image analysis. It includes a signature acquisition device 101, an image acquisition device 100, a processing unit 102, and a storage unit 104. The image acquisition device 100 can be a camera or any device with image acquisition capabilities, used to acquire images. The image acquisition device 100 should be positioned appropriately to clearly capture the signer's hand movements and the signing process. The signature acquisition device 101 can be an electronic signature pad, a touch panel, a pressure-sensing plate, or other device capable of detecting or acquiring handwriting. The processing unit 102 is coupled to the image acquisition device 100 and the signature acquisition device 101, used to receive and process image data from the image acquisition device 100 and handwriting data from the signature acquisition device 101. It can be a microprocessor, a digital signal processor, or other processor with computing power. Storage unit 104 is coupled to processing unit 102 and stores an application program 106, which instructs processing unit 102 to execute a signature verification process 20 to determine the authenticity of the signer's signature through image acquisition and analysis.

[0013] For details, please refer to Figure 2 , Figure 2 This is a schematic diagram of signature verification process 20. Signature verification process 20 includes the following steps: Step 200: Begin.

[0014] Step 201: Use signature acquisition device 101 to acquire handwriting data of a signer during the signing process.

[0015] Step 202: Use the image acquisition device 100 to acquire image data of the signer during the signing process.

[0016] Step 204: Obtain at least one feature information from the image data.

[0017] Step 206: Compare the handwriting data and the at least one feature information with at least one authentication reference data to generate a comparison result.

[0018] Step 208: Based on the comparison result, determine the authenticity of the signature process of the signer.

[0019] Step 210: End.

[0020] According to the signature verification process 20, when the signer signs, the signature verification system 10 collects the signer's handwriting data during the signing process through the signature acquisition device 101 (step 201). Simultaneously, the signature verification system 10 collects image data of the signer's signing process in real time through the image acquisition device 100 (step 202), and the processing unit 102 analyzes the image data of the signing process to obtain its feature information (step 204). Next, the signature verification system 10 compares the collected handwriting data and feature information with pre-stored authentication reference data (step 206) to determine the authenticity of the signer's signing process (step 208). In short, this embodiment of the invention verifies the authenticity of a signature by performing image analysis and comparison on the handwriting data and image data of the signing process. Since the signing process of a signer contains a variety of static or dynamic information, it can reflect the signer's writing habits, multi-dimensional hand features and other personalized characteristics, making it extremely difficult for others to completely imitate. Compared with traditional signature verification mechanisms that can only verify the signer's handwriting, the embodiments of the present invention can greatly improve the accuracy and reliability of signature verification.

[0021] Specifically, in step 201, the signature verification system 10 collects the signer's handwriting data through the signature acquisition device 101. The handwriting data may include, but is not limited to, the two-dimensional spatial coordinates of the handwriting, changes in pressure during writing, the tilt angle between the pen tip and the writing surface, and the trajectory of these changes over time, and is not limited to these. For example, in one embodiment, the signature acquisition device 101 may be implemented using a capacitive touchpad or an electromagnetic induction digital panel, which can detect information such as the pressure, position, and tilt angle of the signer's writing tool (stylus or finger), and can convert the detected information into digital signals. In another embodiment, the signature acquisition device 101 may be configured with a high-resolution sensing array, which can accurately record the trajectory of the pen tip moving on the plane, including the starting point, ending point, and intermediate path points of the strokes, to fully detect the movement characteristics of the signing process. In another embodiment, the signature acquisition device 101 may have pressure sensing capabilities to record changes in the pressure applied by the pen tip to the writing surface during the signing process, which can reflect changes in the force applied by the signer between different strokes. In another embodiment, the signature acquisition device 101 can record the timing information of each stroke, including the writing speed, acceleration changes, and pause time between strokes, to reflect the signer's writing habits and rhythm. In another embodiment, the signature acquisition device 101 can also acquire the tilt angle between the pen tip and the writing plane, which can reflect the signer's pen grip and writing habits, providing additional personal characteristics. The above information can be recorded in real time as the signing process proceeds and converted into digital format for storage as handwriting data for subsequent feature comparison and verification.

[0022] In step 202, the signature verification system 10 uses the image acquisition device 100 to instantly acquire image data of the signer's signing process. In this case, the image acquisition device 100 should be properly set up to ensure complete capture of important information such as the signer's hand movements (relative positions of fingers and knuckles) and signature trajectory (relative movements of fingers and knuckles). The image data can be a continuous dynamic image sequence or a static image acquired at a specific point in time, and is not limited to these. Furthermore, in Figure 1 In the embodiments described, the signature verification system 10 includes only a single image acquisition device 100. However, it is not limited to this and may also include multiple image acquisition devices. For example, in one embodiment, the signature verification system 10 may be equipped with multiple image acquisition devices, and the image acquisition device with the best shooting angle or range may be selected to generate image data of the signing process. In another embodiment, the signature verification system 10 may integrate the images from multiple image acquisition devices to generate image data of the signing process. In yet another embodiment, two or more image acquisition devices may be integrated into one device and have a fixed relative position. Such techniques for generating the required image data using multiple image acquisition devices are well-known to those skilled in the art, and therefore, detailed operation methods will not be described here.

[0023] In step 204, the processing unit 102 analyzes the image data of the signing process to obtain feature information. In one embodiment, the feature information may be the dynamic trajectory of the signer when signing, such as the distance, path, speed, and acceleration of handprints or finger joint movements, or the distance, path, speed, and acceleration of movements between multiple finger joints. For example, please refer to... Figure 3A , Figure 3A This is a schematic diagram of a signature process image captured by the image acquisition device 100. According to... Figure 3A The image showing the signing process illustrates that during the signing process, one of the signer's knuckles A moves along a trajectory RT. Therefore, trajectory RT reflects the signer's personalized characteristics during the signing process and can be used as feature information. The image acquisition device 100 can also simultaneously detect the movement trajectories of multiple knuckles and superimpose these trajectories as feature information. In other words, the processing unit 102 can analyze... Figure 3A The trajectory RT in the signature process image acquired by the image acquisition device 100 is identified as feature information for subsequent comparison.

[0024] In another embodiment, the feature information may be the relative positions of at least three finger joints in three-dimensional space during the signing process, which can reflect the characteristics of the signer's signing posture, such as the relative positions between the metacarpophalangeal joints of the index finger, the proximal phalanx of the index finger, the metacarpophalangeal joints of the middle finger, the proximal phalanx of the middle finger, or the proximal phalanx of the thumb. For example, please refer to... Figure 3B , Figure 3BThis is a schematic diagram of another signature process image captured by the image acquisition device 100. According to... Figure 3B The image showing the signing process illustrates how, during the signing process, the signer's multiple knuckles form a specific polygon, which can be defined by distances L1 to L5. This polygon reflects personalized characteristics such as the signer's pen grip or posture, and thus can be used as feature information. In other words, the processing unit 102 can analyze... Figure 3B The distances L1 to L5 in the signature process images captured by the image acquisition device 100 are identified as feature information for subsequent comparison.

[0025] In another embodiment, the feature information may be the fingerprint features of at least one finger during the signing process, such as the fingerprint features of multiple knuckles, which can also serve as additional identification evidence. For example, please refer to... Figure 3C , Figure 3C This is a schematic diagram of another signature process image captured by the image acquisition device 100. According to... Figure 3C The image showing the signing process reveals specific texture patterns (C1-C4) on multiple knuckles of the signer during the signing process. Therefore, these texture patterns (C1-C4) and their relationships can reflect personalized characteristics such as the signer's pen grip or posture during signing, and thus can be used as feature information. In other words, the processing unit 102 can analyze... Figure 3C The signature process image captured by the image acquisition device 100 identifies the texture patterns C1 to C4 as feature information for subsequent comparison.

[0026] In another embodiment, the feature information may be a static posture at a specific point in time during the signing process, such as the hand state at the start of signing, during signing, and at the end of signing, or the position of the lines on the fingers at a specific point in time, or the relative position between at least three finger joints. For example, please refer to... Figure 3D , Figure 3D This is a schematic diagram of another signature process image captured by the image acquisition device 100. Figure 3D The image showing the signing process depicts the signer's static posture at a specific point in time during the signing process. It can reflect personalized characteristics such as the signer's pen grip or posture, and therefore can be used as feature information. In other words, the processing unit 102 can analyze... Figure 3D The signing process image captured by the image acquisition device 100 identifies the static posture of the signer during the signing process as feature information for subsequent comparison.

[0027] Furthermore, it should be noted that the aforementioned signature process is not limited to whether the signer holds a pen. In some applications, the signer may sign with their finger, and the signature information should be adjusted accordingly for different applications. This should be a skill familiar to those with ordinary knowledge in the field. In other words, regardless of the signature method used, as long as signature information reflecting the signer's writing habits can be collected, it can serve as an important basis for judging the authenticity of the signature, thereby significantly improving security.

[0028] In step 206, the processing unit 102 compares the collected handwriting data and feature information with pre-stored authentication reference data, which may be obtained through various channels. For example, in one embodiment, the signer needs to complete a registration process before signing. For instance, the signer can first use the image acquisition device 100 to collect registration image data of the signing process and obtain registration feature information from it, storing it as authentication reference data. The process of collecting registration image data is not limited to being performed by the image acquisition device 100; it can also be completed by another image acquisition device, such as a mobile phone, laptop, or other electronic device with image acquisition capabilities. In other words, the signer should first use the image acquisition device 100 or other electronic device with image acquisition capabilities to complete the registration process, so that the signature verification system 10 can obtain authentication reference data from the registration image data for comparison in the subsequent signature process.

[0029] It should be noted that the purpose of the registration process is to generate authentication reference data. However, whether to initiate the registration process or its timing and method can be adjusted appropriately according to different needs. For example, in one embodiment, when a signer is performing a signing process, if the signature verification system 10 finds that the signer's authentication reference data has not yet been established, it can automatically initiate the registration process to immediately establish the authentication reference data, allowing the user to complete the one-time registration process and then continue with the original signing operation. However, in higher security application scenarios, the signature verification system 10 may require administrator review and authorization before executing the registration process. This authorization mechanism may include measures such as administrator identity verification, record archiving of approval procedures, and full monitoring of the registration process. In addition, the signature verification system 10 may also require the signer to provide additional identity verification documents during registration, or to complete multiple registration and signing processes within a specific time period, depending on the use case, to establish more complete and reliable authentication reference data.

[0030] In addition to acquiring registration image data via image acquisition device 100 or another image acquisition device to complete the registration process, in another embodiment, authentication reference data may be pre-stored in a database (local or cloud database). The signature verification system 10 can retrieve the authentication reference data stored in the database via data transmission when a comparison is required (i.e., step 206). Furthermore, to ensure data security, the data that the signature verification system 10 needs to access or use for signature verification (such as image data, feature information, authentication reference data, registration image data, registration feature information, etc.) can undergo encryption processing during transmission and storage, for example, using blockchain technology. Correspondingly, if the data has undergone encryption processing, decryption processing is required when accessing or using it; for example, if the authentication reference data has undergone encryption processing, then the comparison of feature information and authentication reference data in step 206 should include the operation of decrypting the authentication reference data.

[0031] On the other hand, since the feature information reflects the hand features of the signer when signing, it can include the dynamic trajectory of the signature, the angle of the fingers, the texture features, the static posture, etc. Therefore, in step 206, appropriate features can be selected as the basis for comparison. Further, in one embodiment, the signature verification system 10 can assign different weights to each feature based on parameters such as image quality and shooting angle. In another embodiment, the signature verification system 10 can incorporate artificial intelligence technology to learn the correlation between multiple signature processes performed by the signer in different postures, in order to adjust the authentication reference data, thereby improving the accuracy and adaptability of the comparison. For example, artificial intelligence technology can learn the correlation between multiple signature processes performed by the signer in standing, sitting, bending over, using a pen, using the index finger, etc., summarize the characteristics of the signer's signature, and generate or adjust the authentication reference data accordingly to improve the comparison accuracy when the signer signs in different postures.

[0032] As can be seen from the different embodiments described above, the feature information obtained from the image data can be dynamic feature information during the signing process or static feature information at a specific point in time during the signing process. In addition, in one embodiment, the signature verification system 10 can integrate handwriting data and feature information based on a timeline to form a composite information, and then compare the composite information with authentication reference data to generate a comparison result. That is, the signature verification system 10 can synchronize and integrate various types of data during the signing process in a temporal sequence. During this process, the signature verification system 10 will pair and combine the handwriting data from the signature acquisition device 101 with the feature information obtained from the image acquisition device 100 according to the time points in which they occur, forming a set of temporally related composite information. For example, handwriting data such as handwriting coordinates, pressure values, and writing speed at a certain point in time during the signing process can be paired with feature information such as finger angles and relative knuckle positions collected at the same time. This pairing process can continue throughout the entire signing process, forming a complete temporal feature sequence from the beginning to the end of the signature. In this way, the signature verification system 10 can capture the dynamic behavioral characteristics of the signer during the signing process, such as analyzing the changes in the signer's finger posture when writing specific strokes, or the coordinated changes in pressure value and hand position when writing at turning points. These temporally correlated features are more personally identifiable and can increase the accuracy of the judgment.

[0033] After the composite information is formed, the signature verification system 10 compares the composite information with the feature information. Since the composite information contains a temporal feature sequence, the comparison process must consider not only the numerical similarity of each feature, but also the consistency of their temporal changes. Such derivative variations should be techniques well known to those skilled in the art.

[0034] On the other hand, during the signing process, the signer's hand movements inevitably obscure the handwriting relative to the image acquisition device 100, and this may vary depending on the pen grip, writing angle, and individual writing habits. In this case, the signature verification system 10 can use the signature acquisition device 101 as the primary source of handwriting data to ensure complete recording of the stroke trajectory during the signing process. While the image acquisition device 100 may not be able to capture all the handwriting completely due to hand obstruction, this partial obstruction can be considered a unique characteristic of the signer. Different pen grips and writing postures will present different obstruction patterns in the image, and these patterns, together with the visible parts of the handwriting, constitute personalized signature characteristics. This characteristic exhibits high consistency and repeatability, especially when the image acquisition device 100 and the signature acquisition device 101 maintain a fixed relative position.

[0035] Furthermore, the partial handwriting captured by the image acquisition device 100 can still be cross-compared with the complete handwriting recorded by the signature acquisition device 101. In other words, the feature information can include the image-captured handwriting that matches the handwriting data. This multi-verification mechanism not only improves the accuracy of signature verification but also provides additional security for anti-counterfeiting identification. The signer's microscopic behavioral characteristics during the signing process, such as changes in pen grip angle, relative positions of finger joints, and dynamic changes in handwriting occlusion, can all be accurately recorded and analyzed through this dual-acquisition method.

[0036] In step 208, the signature verification system 10 determines the authenticity of the signature process based on the comparison results between the handwriting data and / or feature information and the authentication reference data. Furthermore, when the comparison results indicate that the signature is not authentic, the signature verification system 10 can take several measures, such as generating a warning signal (e.g., a visual cue, an audible cue, or a tactile feedback signal), or sending a notification message to a designated receiver or administrator to immediately report the anomaly or trigger other preset security mechanisms. In addition, the signature verification system 10 can dynamically adjust the judgment threshold according to different application scenarios to balance the needs of security and convenience.

[0037] In short, through the signature verification process 20, this embodiment of the invention can not only collect the static features of the signature result (such as handwriting), but also capture dynamic information throughout the entire signing process, such as the speed and force of the signature, habitual pauses during pen strokes, and the stroke order at the end of the stroke—all personalized characteristics. These habitual actions are often long-term and unconscious, making them extremely difficult for others to completely imitate. In addition to writing habits, this embodiment of the invention can also collect multi-dimensional features such as the signer's hand movements, signature trajectory, and finger angles. The combination of these dynamic features further increases the difficulty of forging signatures, significantly improving the accuracy and reliability of verification. Furthermore, this embodiment of the invention can integrate handwriting data and feature information based on a timeline to form composite information, thus enabling a more comprehensive understanding of the signer's signature characteristics, including not only static handwriting shapes but also temporally changing behavioral features, thereby improving the reliability and security of signature verification. This embodiment of the invention can also encrypt and decrypt the data that needs to be accessed or used for signature verification to ensure data security. Furthermore, embodiments of the present invention can also integrate artificial intelligence technology. Through machine learning algorithms, the signature verification system 10 can learn and recognize the signature characteristics of the same person in different situations, such as signature methods using different writing tools or in different postures, thereby improving the accuracy and adaptability of verification. Simultaneously, the signature verification system 10 of the present invention can be implemented on various devices with image acquisition capabilities or electronic devices capable of connecting to external image acquisition devices, including but not limited to personal computers, laptops, or mobile devices.

[0038] Therefore, the signature verification process 20 of this embodiment of the invention can ensure the reliability and security of signature verification through multiple feature analysis, flexible data sources, encryption protection mechanisms, artificial intelligence assistance, and a comprehensive warning system, and can effectively prevent signature forgery, while also providing sufficient flexibility and scalability for practical applications.

[0039] Furthermore, it should be noted that the signature verification process 20 represents the main operating mode of the signature verification system 10. When implementing the signature verification system 10, those skilled in the art should select appropriate components to correctly execute each step of the signature verification process 20 or its derivative variations. Specifically, the processing unit 102 can be a microprocessor, a digital signal processor (DSP), or a microcontroller, while the storage unit 104 can be a read-only memory (ROM), random access memory (RAM), flash memory, or other types of memory devices. The application program 106 is stored in the storage unit 104. When the system starts, the processing unit 102 can read and execute the application program 106 to implement the various functions of the signature verification process 20. In another embodiment, some computationally intensive or time-sensitive functions can be implemented using hardware circuitry, while other more complex logical judgments can be handled by software programs. This hybrid implementation strikes a balance between performance and flexibility, ensuring both system immediacy and good scalability. Regardless of the implementation method, the processing unit 102 must correctly acquire the signals or data acquired by the image acquisition device 100, which can be achieved, for example, through standard communication protocols such as Serial Communication Interface (SCI), Serial Peripheral Interface (SPI), or Inter-Integrated Circuit (I2C).

[0040] On the other hand, the signature verification system 10 uses the image acquisition device 100 to collect image data of the signer's signing process, and performs image analysis and comparison to verify the authenticity of the signature. Therefore, the selection or setting of the image acquisition device 100, such as its placement, angle, sensitivity, focal length, and resolution, should prioritize clearly capturing the signer's hand movements and the signing process. In addition, to ensure that the signer signs in the appropriate position, a specific signature position can be planned in advance based on the shooting characteristics of the image acquisition device 100, or it can be integrated with the signature acquisition device 101 so that the signer can sign in the appropriate position. Furthermore, the signature verification system 10 can also incorporate a prompting mechanism, such as issuing sound or flashing lights when the signer does not sign in the appropriate position to prompt the signer to adjust the signature position.

[0041] The signature capture device 101 is responsible for collecting the handwriting trajectory data of the signer when signing. This can be achieved through high-precision pressure sensing technology, a touchscreen, or other sensing elements to instantly and accurately capture characteristics such as stroke changes, writing speed, and pressure differences during the signing process, converting them into digital handwriting data for subsequent verification and analysis. Therefore, the selection of the signature capture device 101 should consider its sensitivity, resolution, and response speed to writing actions to ensure accurate capture of all writing details of the signer. Furthermore, the signature capture device 101 can be designed with an ergonomic shape for easy operation and can be equipped with a haptic feedback system or display interface to assist the signer in confirming whether their signature action meets the requirements.

[0042] The signature verification system 10 or signature verification process 20 is designed to verify the authenticity of signatures. Those skilled in the art should be able to appropriately apply or implement it in various scenarios requiring identity verification. For example, in a corporate office environment, the signature verification system 10 or signature verification process 20 can be applied to electronic document signing systems to ensure the authenticity of the signatory's identity and can be integrated into the enterprise's information security mechanism as an identity verification method for employees logging into workstations or accessing confidential data. In the financial sector, the signature verification system 10 or signature verification process 20 can be applied to identity verification in bank counter services to improve transaction security; it can also be integrated into mobile banking applications to replace traditional password verification, providing users with a more secure and convenient login method. In the retail sector, the signature verification system 10 or signature verification process 20 can be applied to identity verification in electronic payment systems, especially for authorization confirmation of large transactions; it can also be used in membership card systems, allowing members to quickly complete identity verification through personalized signatures. In the healthcare field, the signature verification system 10 or signature verification process 20 can be used for electronic signing of medical records and prescriptions, ensuring the authenticity and integrity of medical documents; it can also be applied to medical personnel's attendance check-in or operating room access management. In the education field, the signature verification system 10 or signature verification process 20 can be used for identity verification on distance learning platforms, ensuring the identity of students participating in online exams; it can also be used for library borrowing systems or laboratory equipment usage management. In property management, the signature verification system 10 or signature verification process 20 can be used for resident identity verification when entering and exiting buildings, providing higher security than traditional access cards; it can also be used for registration of various public facilities. In the logistics field, the signature verification system 10 or signature verification process 20 can be used for package receipt confirmation, not only recording the recipient's signature but also instantly verifying the recipient's identity. In public sector services, the signature verification system 10 or signature verification process 20 can be used for electronic signing of various government documents, improving administrative efficiency while ensuring the legal validity of documents. These diverse application scenarios demonstrate that this invention can provide a safer and more convenient solution for identity verification needs across various industries.

[0043] In summary, the signature verification system or process provided by this invention captures dynamic features during the signing process in real time using an image acquisition device. It not only includes the static information required for traditional signature comparison but also records the signer's unique writing habits and movement characteristics. During the analysis and comparison of feature information, this invention integrates multiple verification mechanisms, including dynamic trajectory analysis, finger angle recognition, and biometric comparison, and can continuously learn and optimize judgment criteria through artificial intelligence technology. Furthermore, this invention provides comprehensive protection measures for data security, including encrypted data storage and anomaly alert mechanisms, ensuring the reliability of the entire verification process. Therefore, the signature verification system or process of this invention not only effectively prevents signature forgery but also meets the needs of various practical application scenarios, providing a practical and secure solution for identity verification in the digital age.

[0044] The embodiments described above are merely preferred embodiments for fully illustrating the present invention, and the scope of protection of the present invention is not limited thereto. Equivalent substitutions or modifications made by those skilled in the art based on the present invention are all within the scope of protection of the present invention.

Claims

1. A signature verification method based on image analysis, characterized in that, Includes the following steps: A signature collection device is used to collect handwriting data of a signer during the process of signing a signature. An image capture device is used to capture image data of the signer during the signing process; At least one feature information is obtained from the image data; The handwriting data and the at least one feature information are compared with at least one authentication reference data to generate a comparison result; and Based on the comparison results, the authenticity of the signature process by the signer is determined.

2. The signature verification method as described in claim 1, characterized in that, The at least one feature information includes at least one of the following: The signer must use at least the angle of one finger when making the signature; The fingerprint features on at least one finger of the signer during the signing process; and The signer must maintain the relative position of at least three finger joints during the signing process.

3. The signature verification method as described in claim 2, characterized in that, The at least one feature is either a dynamic feature during the signing process or a static feature at a specific point in time during the signing process.

4. The signature verification method as described in claim 1, characterized in that, Further includes: The handwriting data and at least one feature information are integrated based on the timeline to form a composite information, and then the composite information is compared with the at least one authentication reference data to generate the comparison result.

5. The signature verification method as described in claim 1, characterized in that, The at least one feature information includes: A partially obscured character is obtained by comparing the image data with the handwriting data.

6. A signature verification system based on image analysis, characterized in that, Include: A signature capture device used to capture handwriting; An image acquisition device used to acquire images; A processing unit is coupled to the signature acquisition device and the image acquisition device; A storage unit, coupled to the processing unit, stores an application that instructs the processing unit to execute a signature verification method, the signature verification method comprising the following steps: The signature collection device is used to collect handwriting data of a signer during the process of signing a signature. The image acquisition device is used to capture image data of the signer during the signing process; At least one feature information is obtained from the image data; The handwriting data and the at least one feature information are compared with at least one authentication reference data to generate a comparison result; and Based on the comparison results, the authenticity of the signature process by the signer is determined.

7. The signature verification system as described in claim 6, characterized in that, The at least one feature information includes at least one of the following: The signer must use at least the angle of one finger when making the signature; The fingerprint features on at least one finger of the signer during the signing process; and The signer must maintain the relative position of at least three finger joints during the signing process.

8. The signature verification system as described in claim 6, characterized in that, The at least one feature is either a dynamic feature during the signing process or a static feature at a specific point in time during the signing process.

9. The signature verification system as described in claim 6, characterized in that, This signature verification method also includes: The handwriting data and at least one feature information are integrated based on the timeline to form a composite information, and then the composite information is compared with the at least one authentication reference data to generate the comparison result.

10. The signature verification system as described in claim 6, characterized in that, The at least one feature information includes: A partially obscured character is obtained by comparing the image data with the handwriting data.

Images