Certificate Authenticity Verification Using Static and Dynamic Features
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Solution Overview
Problem
Existing certificate authenticity identification methods suffer from low accuracy due to reliance on subjective human judgment and lack of standardized, scientific verification processes, particularly when dealing with forged certificate images.
Innovation Solution
A method that identifies certificate authenticity by detecting both static and dynamic anti-counterfeiting points in multiple images, extracting image feature information and variation features, using a three-dimensional convolutional network to determine authenticity results, and combining these results for improved accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If subjective human judgment is used for certificate verification, then the process is simple to implement, but the identification accuracy is low
Solution Approach 1:
The patent replaces subjective human judgment with an automated computer-based verification system that uses image processing algorithms to detect static and dynamic anti-counterfeiting points. This substitution of mechanical/manual verification with automated computational methods directly improves identification accuracy while maintaining operational simplicity through standardized algorithmic processes.
Solution Approach 2:
The patent introduces an intermediary verification system that acts between the certificate image and the final authenticity determination. This intermediary layer processes images through multiple detection stages (static point detection, dynamic point detection across multiple frames, feature extraction) to provide objective, standardized verification that improves accuracy without requiring complex manual intervention at each step.
2Measurement precision
If only static anti-counterfeiting points are used for verification, then the verification process is faster, but the identification accuracy is insufficient
Solution Approach 1:
The patent transitions from static-only verification to dynamic verification by capturing multiple certificate images at different time points and detecting dynamic anti-counterfeiting points that change across frames. This dynamic approach improves identification accuracy by verifying temporal consistency of anti-counterfeiting features while maintaining efficiency through automated batch processing of multiple images.
Solution Approach 2:
The patent performs preliminary detection of static anti-counterfeiting points in the first frame before proceeding to dynamic point detection across subsequent frames. This preliminary action allows the system to quickly establish baseline verification and only perform more time-consuming dynamic analysis when necessary, optimizing the balance between verification time and accuracy.
3Measurement precision
If multiple certificate images are captured and analyzed, then the identification accuracy improves, but the processing complexity increases
Solution Approach 1:
The patent segments the verification process into distinct modular stages: static point detection in first frame, dynamic point detection in subsequent frames, feature extraction, and authenticity determination. This segmentation of the multi-image analysis process into independent processing modules reduces overall complexity by allowing each stage to be optimized and executed separately while maintaining high identification accuracy through comprehensive analysis.
Data Source
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AI summary
A certificate authenticity identification method and apparatus, a computer-readable medium, and an electronic device. The certificate authenticity identification method comprises: detecting dynamic anti-counterfeiting points and static anti-counterfeiting points comprised in a plurality of certificate images of a target certificate, the plurality of certificate images being obtained by performing image acquisition on the target certificate at different angles (S210); extracting image feature information of positions where the static anti-counterfeiting points are located to obtain static anti-counterfeiting point features, and extracting image feature information of positions where the dynamic anti-counterfeiting points are located and change feature information of the dynamic anti-counterfeiting points among the plurality of certificate images to obtain dynamic anti-counterfeiting point features (S220); identifying, on the basis of the static anti-counterfeiting point features, a first authenticity result corresponding to the static anti-counterfeiting points, and identifying, on the basis of the dynamic anti-counterfeiting point features, a second authenticity result corresponding to the dynamic anti-counterfeiting points (S230); and determining the authenticity of the target certificate according to the first authenticity result and the second authenticity result (S240). Thus, the authenticity of the target certificate can be identified by combining the first authenticity result of the static anti-counterfeiting points with the second authenticity result of the dynamic anti-counterfeiting points, so that the authenticity of a certificate can be accurately identified.