The volume of digital images generated and uploaded on the internet every day by the scientific, medical, educational, industrial and other communities are very large. The problem of retrieving the desired images from huge collections is a major problem. The user queries are becoming very specific and traditional text-based methods cannot efficiently handle them. The subjectivity of human perception and the rich contents of the images further aggravate the problem. To overcome this problem, a new query-by-example technique using multiple color, texture and shape features is proposed and evaluated in this paper. The experimental results suggest that our proposed technique is efficient and retrieves semantically more similar images.
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