Content-based image retrieval using color tuple histograms

Color histograms have been shown to be very effective in representing images for content- based retrieval systems. They are compact, robust and amenable to computer analysis. However, such histograms convey only global image properties and do not embody local color information which is so important when comparing and contrasting images. We present a novel image coding scheme which captures some of this locally correlated color information and improves the selectivity of the retrieval mechanism -- an important issue for very large databases. The technique uses a histogram of features which represent frequently occurring local combinations color tuples occurring throughout the image. It outperforms straight color histogram matching. We outline the thrust of our approach and discuss the factors affecting the efficacy of the retrieval mechanism using a database of color images.