In this paper, a novel region-based multiple classifier color image retrieval system is presented. In our approach, a region-growing technique is first employed to cluster connected color pixels with the same color in an image to form color regions which are the primitive elements utilized in our proposed approach. Then, three complementary region-based classifiers that we developed are selected in the classifier selection stage, which include color classifier, shape classifier, and relational classifier. In each classifier, a virtue probability representing the probability that an image is similar to the query image is defined. Thereafter, a set of virtue probabilities is calculated in each classifier. Next, the measurement dependent methods are applied to combine the virtue probabilities of classifiers in the decision combination stage. The dynamic selection scheme designed in the decision combination stage can further improve the system performance dramatically. Experimental results reveal the feasibility and validity of our proposed approach in solving color image retrieval problem.