Abstract— To improve the accuracy of image matching shoeprint image feature matching method based on PCA-SIFT is proposed. Firstly, feature detection and pre-matching of images are done by using PCA-SIFT (principal component analysis-scale invariant feature transform) algorithm. And then, the correlation coefficient is used as similarity measurement, which can filter image interest points. By this method, the image matching pairs can be obtained. Finally, the RANSAC (random sample consensus) algorithm is used to eliminate the mismatching pairs. The simulation results demonstrate that the proposed algorithm is more robust while maintaining good registration accuracy when analyzing partial shoeprint images in the presence of geometric distortions such as scale and rotation distortions compared with conventional algorithms.
Keywords— PCA-SIFT, shoeprint image, image matching, RANSAC.
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