Abstract
In this paper, SIFT feature extraction algorithm was optimized through image filtering, so as to highlight the role of stable edge corner and improve the efficiency of stable edge corner collection. Afterwards, the experimental results were compared and verified by the FLANN feature matching method. Experimental results show that the improved SIFT feature extraction algorithm using image filtering can improve the extraction effect of feature points with stable edge response, while suppressing the extraction of feature points with unstable edge response, thus improving the accuracy of matching.
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