Multi-Angle Palm Feature Fusion for Accurate Identity Authentication
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Solution Overview
Problem
Traditional palm recognition methods based on single-angle palm images are limited by low accuracy and inefficient use of hardware resources due to the limited feature information used in identity authentication, leading to suboptimal performance.
Innovation Solution
A method that acquires multiple palm images at different angles, positions the palm key region, assigns higher weights to this region during feature extraction, and fuses these features to generate a multi-angle palm feature for enhanced identity authentication, utilizing artificial intelligence for improved accuracy and resource efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a single-angle palm image is used for identity authentication, then the system complexity is low, but the authentication accuracy is limited due to insufficient feature information
Solution Approach 1:
The patent transitions from single-angle (2D) palm image recognition to multi-angle (3D/spatial) palm image recognition. By capturing palm images from multiple angles (front view, side views, top views) and fusing features across these different spatial dimensions, the system obtains comprehensive three-dimensional palm feature information, significantly improving authentication accuracy while maintaining reasonable system complexity through software-based feature fusion.
Solution Approach 2:
The patent merges multiple single-angle palm images into a comprehensive multi-angle palm feature representation. By combining feature vectors from different viewing angles through fusion operations (concatenation, averaging, or learned fusion), the system creates a richer feature set that captures palm characteristics from multiple perspectives, resolving the contradiction between using simple single-angle images and achieving high accuracy.
2Measurement precision
If multiple palm images at different angles are acquired and processed, then the authentication accuracy improves, but the hardware resource requirements increase
Solution Approach 1:
The patent uses software-based feature extraction and fusion algorithms to process multiple palm images, replacing the need for multiple physical hardware sensors. Instead of requiring separate cameras or sensors for each angle, the system captures images using a single device and uses computational methods to extract and fuse features from multiple angles, significantly reducing hardware resource requirements while maintaining high authentication accuracy.
Solution Approach 2:
The patent replaces potential mechanical/multiple-sensor systems with a computational image processing system. By using algorithms for feature extraction, angle detection, and feature fusion, the system achieves multi-angle recognition capabilities through software rather than hardware, reducing the quantity of physical hardware resources needed while improving authentication accuracy.
3Loss of information
If feature extraction is performed on the entire palm image, then comprehensive features are obtained, but the processing time increases
Solution Approach 1:
The patent segments the palm image into multiple regions of interest (ROIs) such as the palm center, finger roots, and palm lines. By performing feature extraction on these segmented regions rather than the entire image, the system reduces the computational workload and processing time while still capturing comprehensive palm features. The segmentation allows parallel processing of different regions and focuses computational resources on the most discriminative areas.
Solution Approach 2:
The patent applies different processing priorities to different regions of the palm image. By identifying and prioritizing key regions (such as palm lines, finger roots, and central palm area) that contain the most discriminative features for authentication, the system performs more intensive feature extraction on these local areas while using lighter processing for less critical regions, thereby reducing overall processing time while maintaining feature information completeness.
Data Source
AI summary
A method for palm feature-based identity authentication is performed by a computer device and the method includes: acquiring a plurality of palm images of a palm at different acquisition angles; for each palm image, positioning a palm key region in the palm image according to an acquisition angle of the palm image and determining an auxiliary region in the palm image except the palm key region; performing feature extraction on the palm image to obtain a single-angle palm feature of the palm image, a contribution weight assigned to the palm key region in the palm image being higher than a contribution weight assigned to the auxiliary region in the palm image; fusing single-angle palm features of the plurality of palm images to obtain a multi-angle palm feature of the palm; and performing identity authentication using the multi-angle palm feature.