Identity Document Authentication Using Multi-Resolution Frequency Maps
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Solution Overview
Problem
Existing methods for determining the authenticity of identity documents are inadequate in extracting features, are sensitive to noise and variations in image capture conditions, and lack computational efficiency, making it difficult to detect fraudulent documents.
Innovation Solution
The method employs multi-resolution convolution and octave convolution techniques to extract first and second frequency components from identity document images, comparing them against frequency maps to determine authenticity, using high and low pass filters to isolate relevant frequency information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If octave convolution techniques are used to process identity document images, then multiple spatial frequencies can be represented simultaneously, but feature extraction from identity documents is inadequate and information exchange between different resolutions is unsatisfactory
Solution Approach 1:
The patent segments the identity document verification process into multiple frequency components using multi-resolution convolution and octave convolution. The system divides the feature extraction into different spatial frequency ranges, processing low-frequency and high-frequency components separately through dedicated convolutional layers, then combines them to achieve both precise feature extraction and robustness to noise
Solution Approach 2:
The patent introduces multi-resolution analysis as an additional dimension to the traditional single-resolution processing. By representing the identity document at multiple spatial resolutions simultaneously through octave convolution, the system extracts features from different frequency bands, enabling better information exchange between resolutions and improved overall verification accuracy
2Reliability
If traditional image analysis methods are used, then the process is simpler, but the system is sensitive to noise and variations in conditions during image capture
Solution Approach 1:
The patent implements a dynamic multi-resolution processing system that adapts to different input conditions. The octave convolution architecture dynamically processes features at multiple spatial frequencies, allowing the system to maintain robustness to noise and variations while managing computational complexity through efficient gradient flow across resolutions
Solution Approach 2:
The patent introduces frequency maps as intermediary structures that mediate between the captured identity document image and the final verification decision. These frequency maps, created from verified documents, serve as reference intermediaries that enable robust comparison while reducing the direct impact of noise and capture condition variations
3Productivity
If manual analysis methods are used, then computational resources are reduced, but productivity and authentication speed are lower
Solution Approach 1:
The patent replaces manual analysis mechanics with automated multi-resolution convolutional processing. The system uses octave convolution to automatically extract and compare frequency components, eliminating the need for manual inspection while maintaining high authentication speed and reducing processing time through parallel processing at multiple resolutions
Data Source
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AI summary
A method for determining the authenticity of an identity document is provided that includes capturing, by an electronic device, image data of an identity document, determining a class of the identity document, and extracting, using multi-resolution convolution and octave convolution techniques, first and second frequency components from the captured image data. The first and second frequency components correspond to different spatial frequency ranges. Moreover, the method includes determining whether the first and second frequency components satisfy matching criteria with data in corresponding frequency maps. The frequency maps are created from verified documents belonging to the determined class of document. In response to determining at least one of the first and second frequency components satisfies the matching criteria, determining the identity document is genuine.