An objective performance evaluation tool for color based image retrieval systems
This study addresses the problem of the objective performance evaluation of image retrieval systems. Considering the color feature, a tool for synthetic image databases generation is proposed. This allows to control the number and location of the dominant colors in the Lab space and provides also their spatial coherency. It is then possible to sort exactly the images for the color feature. We also propose a new similarity measure to compare images described by the color feature. Based on the assumption of a Gaussian distribution for each dominant color, each image is modeled by the sum of these Gaussian distributions. The similarity measure performs a Kullman's distance between two modeled distributions. The objective performance evaluation based on the synthetic database is done for comparing our image retrieval system (IMALBUM) which uses the new similarity measure and MPEG7 approach. Experiments on MPEG7 database are also presented as a subjective evaluation and discussed.