An Image Segmentation Approach with Progressive Superpixel Merging

被引：0

作者：

Yu H. ^{[1
,2
]}

Zhang W. ^{[1
]}

Yang Z. ^{[1
,2
]}

Li S. ^{[1
]}

Wan Q. ^{[1
]}

Lin A. ^{[1
]}

机构：

[1] College of Electrical and Information Engineering, National Engineering Laboratory of Robot Visual Perception and Control Technology, Hunan University, Changsha

[2] Shenzhen Research Institute of Hunan University, Shenzhen

来源：

Hunan Daxue Xuebao/Journal of Hunan University Natural Sciences | 2018年 / 45卷 / 10期

基金：

中国国家自然科学基金;

关键词：

Earth mover's distance; Image segmentation; Region merging; Superpixel; Weibull mixture model;

D O I：

10.16339/j.cnki.hdxbzkb.2018.10.017

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

Traditional image segmentation methods based on superpixel still have many problems in terms of consistency of edge segmentation, computational efficiency and adaptability of merging algorithms. We combine domestic and foreign research advances and propose a novel superpixel merging image segmentation method, which adopts ERS superpixel over-segmentation algorithm and uses intensity and gradient histogram as superpixel features. Additionally, EMD method is used to calculate feature distance and the merging self-adaptive threshold is obtained by mixing Weibull model to complete the segmentation. As a result, the time complexity of proposed algorithm is reduced to O(N), and the segmentation process is not required to manually select the region to be segmented. Compared with current methods, experiment results show that the proposed method has better performance on boundary accuracy and processing efficiency. © 2018, Editorial Department of Journal of Hunan University. All right reserved.

引用

页码：121 / 129

页数：8

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