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_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%.