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Content-based image retrieval (CBIR), also known as query by image content (QBIC) and content-based visual information retrieval (CBVIR) is the application of computer vision to the image retrieval problem, that is, the problem of searching for digital images in large databases. It is increasingly evident that an image retrieval system has to be domain specific. In this paper, we present an algorithm for retrieving images with respect to a database consisting of difference class of images. The feature vectors used are DCT coefficient arranged in a typical fashion. Image similarity is computed using k-means clustering followed by the modified chi-square distance measure.