Explore MATLAB source code curated for "匹配算法" with clean implementations, documentation, and examples.
Implementation of post-processing fingerprint feature extraction and matching algorithms for fingerprint recognition, featuring custom .m files for enhanced performance when integrated with preprocessing stages - includes key functions for minutiae detection, similarity scoring, and template comparison
The SIFT feature point correspondence matching algorithm is valuable for both beginners and experienced programmers in stereo matching, offering robust implementation approaches and feature descriptor analysis techniques.
Wavelet Transform-based Multiresolution Matching Algorithm: This algorithm leverages wavelet multiresolution properties to decompose both the target image and template image into Z layers while preserving only the LL low-frequency components. It employs normalized correlation as a similarity metric to perform coarse-to-fine correlation matching, where each subsequent layer uses matching results from the previous layer to conduct localized searches in higher-resolution spaces. This approach significantly reduces search space and decreases computational load for similarity calculations in each matching iteration. Implementation typically involves wavelet decomposition using functions like wavedec2() in MATLAB, with correlation computed through optimized matrix operations.
A MATLAB-implemented template matching algorithm designed for polygon approximation matching using contour extraction techniques, featuring image processing and geometric analysis capabilities.