Skin Pattern Extraction Using 3D Luminance Depth Analysis
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Solution Overview
Problem
Current biometric authentication systems based on skin patterns face challenges in enhancing the accuracy of biometric information processing, particularly in capturing the depth and complexity of skin patterns effectively.
Innovation Solution
An information processing apparatus that acquires first and second feature amounts from three-dimensional luminance data, with the first feature amount from a surface plane and the second from a depth direction, to calculate an extraction depth for pattern extraction, thereby improving the accuracy of skin pattern recognition.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If only surface luminance data is used for skin pattern extraction, then the processing is simple, but the accuracy of biometric information is insufficient
Solution Approach 1:
The patent transitions from two-dimensional surface luminance data to three-dimensional data by incorporating depth information. The system extracts not only surface patterns but also subsurface patterns at different depths, thereby enhancing the accuracy of biometric information extraction without significantly increasing processing complexity.
Solution Approach 2:
The patent segments the skin pattern extraction into multiple depth layers. By dividing the three-dimensional luminance data into different depth ranges (surface layer and subsurface layers), the system can independently analyze and extract features from each layer, improving overall accuracy while maintaining manageable processing complexity through structured data organization.
2Measurement precision
If three-dimensional luminance data with depth information is used, then the accuracy of skin pattern recognition is improved, but the complexity of feature amount acquisition increases
Solution Approach 1:
The patent performs preliminary processing by pre-defining multiple depth ranges and preparing corresponding feature extraction parameters in advance. This allows the system to efficiently query and extract features from three-dimensional luminance data without performing complex real-time calculations, thus improving recognition accuracy while managing the complexity of feature acquisition through pre-computed depth-based feature maps.
3Reliability
If extraction depth is calculated based on multiple feature amounts from different planes, then the reliability of authentication is improved, but the calculation processing becomes more complex
Solution Approach 1:
The patent merges multiple feature amounts extracted from different depth planes and surface orientations into a unified extraction depth calculation. By combining surface luminance features with subsurface depth features through a integrated calculation method, the system achieves more reliable authentication while avoiding redundant separate processing steps.
Solution Approach 2:
The system uses feedback from feature amount analysis at different depths to iteratively refine the extraction depth calculation. By continuously adjusting the extraction depth based on the strength and quality of features detected at various depths, the system improves authentication reliability through adaptive depth selection without requiring exhaustive search through all possible depth values.
Data Source
AI summary
There is provided an information processing apparatus including a first acquisition means for acquiring a first feature amount acquired from luminance data of a first plane facing a surface of a skin among three-dimensional luminance data of the skin, a second acquisition means for acquiring a second feature amount acquired from luminance data of a second plane including a depth direction of the skin among the three-dimensional luminance data, and a calculation means for calculating an extraction depth for extraction of a pattern of the skin based on the first feature amount and the second feature amount.