Content-based image retrieval using color and pattern histogram adaptive to block classification characteristics

We propose a new content-based image retrieval method using the color and pattern histogram that is adaptive to the block classification characteristics. In the proposed method, the color and pattern feature vectors are extracted according to the characteristics of the block classification after dividing an image into the blocks with a fixed size. Specifically, the adaptive representative color histograms are calculated according to the statistical characteristics of the classified block and the directional pattern histograms are extracted by performing the directional pattern classification. Experimental results show that the proposed method can outperform the conventional methods as regards the precision.