A Continuous Probabilistic Framework for Image Matching

In this paper we describe a probabilistic image matching scheme in which the im age representation is continuous and the similarity measure and distance computation are also de ned in the continuous domain Each image is rst represented as a Gaus sian mixture distribution and images are compared and matched via a probabilistic measure of similarity between distributions A common probabilistic and continuous framework is applied to the representation as well as the matching process ensuring an overall system that is theoretically appealing Matching results are investigated and the application to an image retrieval system is demonstrated