Quantitative assessment of qualitative color perception in image database retrieval

We propose a multiresolution indexing algorithm based on color histogram which exploits the wavelet decomposition and a customized quantization for content-based image retrieval. The aim is to extract automatically the chromatic content of the images and to represent it with simple, robust, efficient and low computational cost descriptors. The proposed method has been integrated for a complete CBIR system, where the classification of images is performed on a qualitative subjective color perception. The system allows testing the semantic and chromatic class homogeneity previously defined by a human observer. Experimental results have been evaluated by the quantitative assessment parameters (averaged precision and recall). Multiresolution proved to be a valid framework to introduce spatiality in color histogram indexing, to dramatically decrease the computational complexity and to validate the qualitative subjective classification