Retrieving similar color images

There is a great demand for efficient tools that can, on the basis of the pictorial content, organize large quantities of images and rapidly retrieve those of interest. With that goal in mind we present a method for indexing complex color images. The basic idea is to exploit image data decomposition and compression based on the standard Haar multiresolution wavelet transform to describe image content. In this way we are able to effectively eliminate data redundancy and concisely represent the salient features of the image in image signatures of predefined lengths. In the retrieval phase image signatures are compared using a similarity measure that the system has 'learned' from user's. Experimental results confirm the feasibility of our approach, which outperforms more standard procedures, in retrieval accuracy and at lower computational costs.