An adaptive approach for color image retrieval
Chih‐Chin Lai, Ying-Chuan Chen · 2011
A content-based image retrieval system adaptable to user's interests through the use of an interactive genetic algorithm is presented in this paper. The mean value and the standard deviation of a color image are used as color features. We also considered the entropy based on the gray level co-occurrence matrix and the edge histogram descriptor as the texture features. Moreover, a wavelet-based descriptor which is used to extract texture features of an image is also proposed. Further, in order to bridge the gap between the retrieving results and the users' expectation, the interactive genetic algorithm is employed such that users can adjust the weight for each image according to their expectations. Experimental results are provided to illustrate the feasibility of the proposed approach.