Abstract
Most object recognition schemes fail in case of illumination changes between the color image acquisitions. One of the most widely used solutions to cope with this problem is to compare the images by means of the intersection between invariant color histograms. The main originality of our approach is to cope with the problem of illumination changes by analyzing each pair of query and target images constructed during the retrieval, instead of considering each image of the database independently from each other. In this paper, we propose a new approach which determines color histograms adapted to each pair of images. These adapted color histograms are obtained so that their intersection is higher when the two images are similar than when they are different. The adapted color histograms processing is based on an original model of illumination changes based on rank measures of the pixels within the color component images.
Highlights
IntroductionObject searching in a database of color images, which is aparticular problem of color image retrieval, is identical to appearance-based object recognition
We propose to demonstrate the improvement of the intersection between the pairs of adapted color histograms for object recognition purpose across illumination changes
We propose to consider each pair constituted by the query image and one of the target images instead of determining invariant color histograms for each image of the database
Summary
Object searching in a database of color images, which is aparticular problem of color image retrieval, is identical to appearance-based object recognition In this framework, the recognition problem can be stated in terms of finding among all the target images of a database, those which contain the same object as that represented by the query image. The recognition problem can be stated in terms of finding among all the target images of a database, those which contain the same object as that represented by the query image Each of these images contains one single object placed on a uniform background. In this context, the image indexing scheme consists in extracting robust and efficient characteristic indices from the target and query images. The target images are ranked with respect to their similarity measures with the query image, in order to determine those which contain the same object as that represented by the query image
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