Constraint adaptive segmentation for color image coding and content-based retrieval
We present a constraint adaptive image segmentation technique designed to achieve the combined purposes of color image coding/compression, indexing and content-based retrieval. An image is segmented into homogeneous squared regions of variable sizes such that it can be encoded very efficiently. From the segmented image, we derive an effective and efficient image content description feature termed the region and color co-occurrence matrix (RACOM) as image index for content-based indexing and retrieval. Experimental results are presented to demonstrate that RACOM is a very effective image content description feature and has comparable performance to state of the art methods, colour correlogram and MPEG7 colour structure histogram, in content-based image retrieval from large image databases.