Image retrieval by texture similarity

Accuracy and efficiency are the two important issues in designing content-based image retrieval systems. In this paper, we present an efficient image retrieval system with high performance of accuracy based on two novel features, the composite sub-band gradient vector and the energy distribution pattern string. Both features are generated from the sub-images of a wavelet decomposition of the original image. A fuzzy matching mechanism based on energy distribution pattern strings serves as a filter to quickly remove undesired images in the database from further consideration. The images passing the filter will be compared with the query image based on composite sub-band gradient vectors which are extremely powerful for discriminating detailed textures. Through several extensive experiments by exercising our prototype system with a database of 2400 images, we demonstrated that both high accuracy and high efficiency can be achieved at the same time by our approach.