Content-based image retrieval using colour n-grams

Colour 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 colour information which is so important when comparing and contrasting images. We present a novel image coding scheme which captures some of this locally correlated colour 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 local combinations of colour artifacts within an image, called colour n-grams. We outline the thrust of our approach and discuss the factors affecting the efficacy of the retrieval mechanism using a database of colour images.