Image feature hierarchical index method for large image

Abstract

Aiming at the hierarchical index method of large image features, the hierarchical index structure of large image is established by using the global position constraint information of large image. This method combines LSH algorithm and KD tree algorithm based on location information. It can control the space complexity of LSH algorithm and the time complexity of KD tree algorithm in high-dimensional feature retrieval. It can speed up the search speed and improve the accuracy of finding the nearest neighbor features, so as to obtain the best comprehensive search performance compared with LSH algorithm and KD tree algorithm. This method mainly includes three steps: extracting thumbnail to build twolayer pyramid image index structure, using LSH algorithm to search rough position for thumbnail, and using KD tree algorithm based on position information to search feature points near neighbor for original image.