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Image segmentation with searching tree of superpixel boundaries
Author(s): Eisaku Ono; Ikuko Shimizu
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Paper Abstract

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.

Paper Details

Date Published: 22 March 2019
PDF: 6 pages
Proc. SPIE 11049, International Workshop on Advanced Image Technology (IWAIT) 2019, 110493V (22 March 2019); doi: 10.1117/12.2521577
Show Author Affiliations
Eisaku Ono, Tokyo Univ. of Agriculture and Technology (Japan)
Ikuko Shimizu, Tokyo Univ. of Agriculture and Technology (Japan)


Published in SPIE Proceedings Vol. 11049:
International Workshop on Advanced Image Technology (IWAIT) 2019
Qian Kemao; Kazuya Hayase; Phooi Yee Lau; Wen-Nung Lie; Yung-Lyul Lee; Sanun Srisuk; Lu Yu, Editor(s)

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