Content-based Image Retrieval Using Entropy and Fractal Coding

摘要

Describing and extracting image's feature is a key question in content-based image retrieval system, and this paper puts forward a novel image retrieval method using image information entropy and fractal coding. First, compared with a given threshold computed from the inquired image, each image in the database is classified by computing its image entropy. Second, the inquired image's fractal coding is got by Jacquin method, which is applied to the same kind of database images with fractal tenth iteration decoding. Finally, image retrieval result is obtained by matching the similar Euclidean distance between the inquired image and the iterated decoded image. Experimental results show that compared with the direct image pixels similar matching strategy, our scheme improves the retrieval time greatly and guarantees the retrieval accuracy, thus our proposed method is effective and feasible.