A New Content-Based Image Retrieval Using the Multidimensional Generalization of Wald-Wolfowitz Runs Test

抄録

This paper proposes two new similarity measures for the content-based image retrieval (CBIR) systems. The similarity measures are based on the k-means clustering algorithm and the multidimensional generalization of the Wald-Wolfowitz (MWW) runs test. The performance comparisons between the proposed similarity measures and a current CBIR similarity measure based on the MWW runs test were performed, and it can be seen that the proposed similarity measures outperform the current similarity measure with respect to the precision and the computational time.