On image segmentation for object-based image retrieval

We describe a new approach to image segmentation to improve object-based image retrieval. This method partitions color images automatically into disjointed meaningful regions by integrating the contour-based analysis with the region-based analysis. It evaluates the description length of each region and groups multiple regions to form a larger region to minimize the total description length. Through this process, it can distinguish the object boundaries from the edge of the texture. The system successfully extracts the semantically meaningful objects, which meet the segmentation guideline for object-based image retrieval. We have built a system based on this new approach to image segmentation and applied it to a personal photograph database for evaluation. Retrieval results show usefulness and confirm the effectiveness of the proposed methods.