Using a probabilistic source model for comparing images

We propose a probabilistic model for image retrieval. To obtain the similarity between the query image IQ and any image I' in the collection, the model computes the probability of generating the image I' given the observation of the query image I/sub Q/. We compare our probabilistic model for image retrieval with a color histogram based image retrieval method and the IBM QBIC image search engine. The evaluation used the 11-hour video retrieval collection (80,000 extracted images) and associated queries from the 2001 TREC-10 information retrieval evaluations. The experimental results show that the probabilistic model dramatically outperforms the color histogram based image retrieval method and the IBM QBIC image search engine by 40%.