Image segmentation with searching tree of superpixel boundaries
Eisaku Ono, Ikuko Shimizu · International Workshop on Advanced Image Technology (IWAIT) 2019 · 2019
Image segmentation is one of the most important techniques in computer vision and image processing. Many image segmentation methods have been proposed for these few decades. Hierarchical Feature Selection (HFS)1 is a graph-based approach for the image segmentation. It is known as a fast segmentation method that merges over segmented regions hierarchically. At the first level of the merge, the superpixels are utilized to obtain the over segmented regions. However, HFS sometimes fails when it is applied for the textured regions. In this paper, we propose a new approach for image segmentation, Searching Tree Segmentation from Superpixel (STSS), by formulating the merge of superpixels as a path searching problem. We construct trees and search the trees whose nodes correspond to the boundary of the superpixels and values of the nodes correspond to the distance between superpixels. Our algorithm does not check the boundaries of similar superpixels if these are no neighboring boundaries of the distinctively different superpixels to prevent the over segmentation of the textured regions, while HFS checks all boundaries including quite similar superpixels.