標題: Hierarchical Image Segmentation Based on Iterative Contraction and Merging
作者: Syu, Jia-Hao
Wang, Sheng-Jyh
Wang, Li-Chun
電機學院
電信工程研究所
College of Electrical and Computer Engineering
Institute of Communications Engineering
關鍵字: Affinity matrix;contraction process;hierarchical image segmentation
公開日期: 1-五月-2017
摘要: In this paper, we propose a new framework for hierarchical image segmentation based on iterative contraction and merging. In the proposed framework, we treat the hierarchical image segmentation problem as a sequel of optimization problems, with each optimization process being realized by a contraction-and-merging process to identify and merge the most similar data pairs at the current resolution. At the beginning, we perform pixel-based contraction and merging to quickly combine image pixels into initial region-elements with visually indistinguishable intra-region color difference. After that, we iteratively perform region-based contraction and merging to group adjacent regions into larger ones to progressively form a segmentation dendrogram for hierarchical segmentation. Comparing with the state-of-the-art techniques, the proposed algorithm can not only produce high-quality segmentation results in a more efficient way, but also keep a lot of boundary details in the segmentation results.
URI: http://dx.doi.org/10.1109/TIP.2017.2651395
http://hdl.handle.net/11536/145376
ISSN: 1057-7149
DOI: 10.1109/TIP.2017.2651395
期刊: IEEE TRANSACTIONS ON IMAGE PROCESSING
Volume: 26
起始頁: 2246
結束頁: 2260
顯示於類別:期刊論文