A COLOR-BASED IMAGE REPRESENTATION AND GLOBAL SIMILARITY MATCHING FOR COLOR IMAGES

The retrieval of images based on their similarity to an example image is an important and fascinating area of research. In this paper, an image representation technique to characterize visual appearance for determining global similarity in images is described. Based on the analysis of the color spaces, color invariants are computed from images, which are transformed by using the DFT. Then, the PCA-based dimensionality reduction is used, and the dimensionality-reduced vectors are used as the image representation for similarity matching. A metric of similarity between images is defined, allowing to perform retrieval by using the above representation. Experimental results are reported and presented to demonstrate the effectiveness and efficiency of the proposed approach.