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Superpixel Based Hierarchical Segmentation for Color Image
Chong WU Le ZHANG Houwang ZHANG Hong YAN
IEICE TRANSACTIONS on Information and Systems
Publication Date: 2020/10/01
Online ISSN: 1745-1361
Type of Manuscript: LETTER
Category: Image Processing and Video Processing
image segmentation, robustness, superpixel,
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In this letter, we propose a hierarchical segmentation (HS) method for color images, which can not only maintain the segmentation accuracy, but also ensure a good speed. In our method, HS adopts the fuzzy simple linear iterative clustering (Fuzzy SLIC) to obtain an over-segmentation result. Then, HS uses the fast fuzzy C-means clustering (FFCM) to produce the rough segmentation result based on superpixels. Finally, HS takes the non-iterative K-means clustering using priority queue (KPQ) to refine the segmentation result. In the validation experiments, we tested our method and compared it with state-of-the-art image segmentation methods on the Berkeley (BSD500) benchmark under different types of noise. The experiment results show that our method outperforms state-of-the-art techniques in terms of accuracy, speed and robustness.