The Research on image retrieval based on PCA-SIFT

This study took butterfly images as the research object, collected and sorted out images of 805 different species of butterflies from 12 families in China, and used local features based on points of interest to describe the characteristics of butterfly images. Two local feature methods, SIFT and PCA-SIFT, were applied to the retrieval of butterfly images. PCA-SIFT used 36-dimension descriptors to describe the points of interest based on SIFT 128-dimension descriptors. Experimental results show that the time complexity of PCA-SIFT based butterfly image retrieval is much lower than SIFT, but the retrieval accuracy is also reduced a lot.