Palm Print Matching Using Orientation Block Segmentation
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Solution Overview
Problem
Traditional fingerprint identification techniques are inefficient for palm print identification due to the larger size and higher pixel count of palm prints, requiring excessive computational resources and being too slow for real-world applications.
Innovation Solution
A two-step process involving orientation image matching to align palm print images followed by minutiae matching, using a coarse-to-fine iterative approach to reduce the number of comparisons and enhance speed and accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional minutiae matching techniques are used for palm print identification, then comprehensive feature comparison is achieved, but processing speed becomes too slow for real-world applications
Solution Approach 1:
The patent divides the palm print image into multiple blocks and performs matching on block pairs rather than the entire image. This segmentation reduces the computational complexity from O(n²) to O((n/k)²) where k is the number of blocks, significantly improving processing speed while maintaining matching accuracy through hierarchical comparison.
Solution Approach 2:
The patent performs orientation field computation and block pair identification as preliminary steps before actual minutiae matching. By pre-processing the orientation fields and identifying candidate block pairs, the system reduces the number of comparisons needed in the subsequent matching stage, thereby improving overall processing speed without sacrificing accuracy.
2Reliability
If exhaustive minutiae comparison is performed across all reference palm prints, then comprehensive identification is achieved, but computational resources become excessively high
Solution Approach 1:
The patent performs matching on a subset of block pairs rather than exhaustively comparing all possible minutiae points across entire palm prints. By selecting and comparing only the most relevant block pairs based on orientation similarity, the system achieves sufficient identification reliability with reduced computational resource consumption.
Solution Approach 2:
The patent segments both the search and reference palm prints into multiple blocks, enabling selective comparison of block pairs. This segmentation allows the system to focus computational resources on promising regions while skipping unlikely matches, thereby reducing overall resource consumption while maintaining identification reliability.
3Measurement precision
If high-resolution comparison is performed on all palm print regions, then matching accuracy is maximized, but processing time increases significantly
Solution Approach 1:
The patent performs coarse-level orientation field comparison at lower resolution as a preliminary step to identify candidate block pairs. Only the promising candidates identified in this preliminary stage undergo fine-level high-resolution comparison, thereby maximizing matching precision while minimizing processing time by avoiding exhaustive high-resolution comparison.
Solution Approach 2:
The patent applies high-resolution comparison only to selected block pairs that show promise at coarser levels, rather than performing high-resolution analysis on all regions. This partial application of high-resolution processing achieves sufficient matching precision while dramatically reducing processing time.
Data Source
AI summary
In some implementations, a method may be used for matching palm print images. A search template that identifies at least a plurality of distinctive search orientation blocks within a search orientation field may be initially generated for a search palm print image. A reference template may be obtained. A mated distinctive reference orientation block may be identified for each of the distinctive search orientation blocks. One or more regions of the search orientation field that include the distinctive search orientation blocks may be compared against one or more corresponding regions of the reference orientation field. An orientation similarity score between the search palm print image and the reference palm print image may be computed based on the comparison. A match may finally be determined if the computed orientation score satisfies a predetermined threshold value.