In large content-based image database applications, e cient information retrieval depends heavily on good indexing structures of the extracted features. While indexing techniques for text retrieval are well understood, e cient and robust indexing methodology for image retrieval is still in its infancy. In this paper, we present a non-hierarchical clustering scheme for index generation using the...

We define a new image feature called the color correlogram and use it for image indexing and comparison. This feature distills the spatial correlation of colors, and is both effective and inexpensive for content-based image retrieval. The correlogramrobustly tolerates large changes in appearance and shape caused by changes in viewing positions, camera zooms, etc. Experimental evidence suggests ...

Image colour is often thought to be an intrinsic correlate of surface re ectance and so is a common feature for image indexing. In this paper we point out that image colour is actually a function of surface re ectance and imaging geometry and the colour of the viewing illuminant. Fortunately methods exist for normalizing away these dependencies. Pixel based and colour channel-based normalizatio...

Fast retrieval using organ shapes is crucial in medical image databases since shape is a clinically prominent feature. In this paper, we propose that 2-D shapes in medical image databases can be indexed by embedding them into a vector space and using efficient vector space indexing. An optimal shape space embedding is proposed for this purpose. Experimental results of indexing vertebral shapes ...