Gaussian mixture model based retrieval technique for lossy compressed color images

With the explosive growth of the World Wide Web and rapidly growing number of available digital color images, much research effort is devoted to the development of efficient content-based image retrieval systems. In this paper we propose to apply the Gaussian Mixture Model for color image indexing. Using the proposed approach, the color histograms are being modelled as a sum of Gaussian distributions and their parameters serve as signatures, which provide for fast and efficient color image retrieval. The results of the performed experiments show that the proposed approach is robust to color image distortions introduced by lossy compression artifacts and therefore it is well suited for indexing and retrieval of Internet based collections of color images stored in lossy compression formats.