A Novel Region Merging Based Image Segmentation Approach for Automatic Object Extraction

This paper presents a novel region merging based automatic image segmentation approach, which is applicable for object extraction. From an initial over-segmentation result, we exploit the regional histogram based similarity measure as merging criterion and merging order determination scheme with three priorities, to efficiently perform region merging, which is recorded using a binary partition tree (BPT). Based on the analysis of BPT, an appropriate subset of BPT nodes is selected to represent a meaningful image segmentation result and object extraction result. Experimental results demonstrate the better segmentation performance of our approach.