Palm Bone Super-Resolution for Reliable Liveness Detection
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Solution Overview
Problem
Existing palm recognition technologies face challenges in accurately distinguishing between living and non-living palm images, particularly due to the ease of imitating palm outlines and prints, leading to insufficient accuracy in living-body detection.
Innovation Solution
The method involves acquiring a first palm bone and joint soft tissue image, performing super-resolution processing to enhance image resolution, and using a living-body detection model to determine whether the image is of a real palm, leveraging the complexity and uniqueness of palm bones and joint soft tissues.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If palm outline and print recognition is used, then the ease of operation is improved, but the reliability of living-body detection deteriorates
Solution Approach 1:
The patent segments the palm recognition system into multiple independent components: palm outline recognition, palm print recognition, and palm bone recognition. Each component processes different features, and their results are combined through fusion to achieve more reliable living-body detection while maintaining ease of operation.
Solution Approach 2:
The patent employs a composite recognition approach by combining multiple recognition methods (outline, print, and bone recognition) into a unified system. This composite strategy leverages the strengths of each method to overcome individual weaknesses, thereby improving overall reliability without sacrificing operational simplicity.
2Device complexity
If simple palm image processing is used, then the device complexity is reduced, but the measurement precision of living-body detection deteriorates
Solution Approach 1:
The patent divides the image processing pipeline into distinct segments: initial image acquisition, super-resolution enhancement, and multi-feature extraction (outline, print, bone). This segmentation allows each module to be optimized independently, maintaining manageable device complexity while achieving high measurement precision through specialized processing at each stage.
Solution Approach 2:
The patent applies super-resolution enhancement as a preliminary action before main recognition processing. This pre-processing step improves the quality of input images, enabling more accurate feature extraction and detection without requiring overly complex subsequent processing, thus balancing device complexity and measurement precision.
3Reliability
If high-resolution palm bone images are used, then the reliability of living-body detection is improved, but the loss of time in processing increases
Solution Approach 1:
The patent performs super-resolution enhancement as a preliminary action to generate high-resolution palm bone images before recognition processing. This pre-generation of high-quality images ensures reliable detection results while allowing the subsequent recognition stage to operate efficiently on prepared data, reducing overall processing time.
Solution Approach 2:
The patent applies super-resolution enhancement selectively to enhance only the critical palm bone regions that are essential for reliable living-body detection. This partial enhancement approach achieves the necessary reliability improvement without processing the entire image at maximum resolution, thereby reducing time loss.
Data Source
AI summary
A method for living-body detection, performed by a computer device, includes acquiring a first image depicting palm bones and joint soft tissues; processing the first image with a super-resolution model to generate a second image having a resolution greater than a resolution of the first image; and providing the second image to a living-body detection model to obtain a discrimination result indicating whether the first image is a living-body palm bone and joint image, wherein the living-body palm bone and joint image is an image obtained by photographing a real palm.