Abstract A novel feature matrix similarity measure method, which is suitable for two dimensional object recognition and matching, is presented. In this method, a similarrow vector is produced by comparing dynamic programming (DP) matching distances, which describe the similarity between the row of a query matrix and those of a sample matrix. And the similarrow vector is used to represent the query matrix. Then the DP matching is again performed to obtain a similarity measure. The proposed method is employed in an image retrieval system using a dominant color feature matrix representation. The experimental results show that the method is efficient.
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2006, Vol. 19 
