Image Segmentation With Unified Region and Boundary Characteristics within Recursive Shortest Spanning Tree

The lack of boundary information in region based image segmentation algorithms resulted in many hybrid methods that integrate the complementary information sources of region and boundary, in order to increase the segmentation performance. In compliance with this trend, we propose a novel method to unify the region and boundary characteristics within the canonical recursive shortest spanning tree algorithm. The main idea is to incorporate the boundary information in the distance metric of RSST with minor changes in the algorithm. Additionally, we still benefit from the simple yet powerful structure of RSST. The results indicate the superiority of the proposed algorithm with respect to the conventional RSST. The object boundaries are successfully preserved. Therefore, the proposed algorithm is a candidate for video object segmentation where object boundaries coincide with motion field boundaries.