This paper proposes Modified Human Colour Perception (MHCPH) based on human visual perception. The colour and gray weights are distributed to neighbouring bins smoothly with respect to pixel information. The amount of weight distributed to the neighbouring bins is estimated using NBS distance, which is for human visual perception of colour. This distribution makes it possible to extract the background colour information effectively along with the foreground information. The low-level feature of all the database images are extracted and stored in feature database. The relevant images are retrieved for a query based on the similarity ranking between the query and database images. In this work, Manhattan distance is used as distance metric. The experimental results are promising and show that the proposed approach identifies relevant images based on the level of smooth distribution even for an image with complex background colour.
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