Image retrieval based on genetic algorithm and information entropy
Ming Zhang · Informationization · 2009
This paper proposed an image retrieval method based on genetic algorithm and information entropy. Firstly, each image was segmented into a constant number of sub-images. The color and texture feature of sub-images were described by information entropy, which made up the entropy tuple. Secondly, the tuple vector of every image was reshuffled in a helix way, to produce the information entropy tuple sequence, which was used in the genetic operations. Finally, the similarity of images was measured by Euclidean distance with the color entropy and texture entropy. Through experiments, it was proved to be effective.