Comparative study of global color and texture descriptors for web image retrieval
Journal of Visual Communication and Image Representation
Perceptual indiscernibility, rough sets, descriptively near sets, and image analysis
Transactions on Rough Sets XV
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This project presents an approach to index and retrieve images using a compact color descriptor in two color spaces namely HSV,and CIE L*u*v*. A compact color descriptor adopted in the proposed content-based image retrieval system is 127-bit binary Haar color histogram, which is used as an index of the images in the database. The color histogram is obtained for an image using a suitable color space. Here, HSV color space, and CIE L*u*v*color space are chosen for comparison. A compact color descriptor is obtained from Haar transform coefficient of the color histogram. Each coefficient is quantized to a binary number, resulting in a 127-bit color descriptor. The descriptors of the images in the database are compared to the descriptor of the query image. The most similar images are retrieved and ordered according to their distances to the query. The proposed retrieval system can effectively retrieve the most similar images in CIE L*u*v* color space. Keywords Compact color descriptor, color spaces, image retrieval.