Fast Image Segmentation Algorithm Based on Superpixel Multi-feature Fusion

被引：0

作者：

Hou X.-G. ^{[1
]}

Zhao H.-Y. ^{[2
]}

Ma Y. ^{[1
]}

机构：

[1] Institute of Network Technology, Beijing University of Posts and Telecommunications, Beijing

[2] School of Computer Science, Beijing University of Posts and Telecommunications, Beijing

来源：

Tien Tzu Hsueh Pao/Acta Electronica Sinica | 2019年 / 47卷 / 10期

关键词：

HOG features; Image segmentation; Multi-feature fusion; Superpixel;

D O I：

10.3969/j.issn.0372-2112.2019.10.014

中图分类号：

学科分类号：

摘要：

In order to improve the efficiency of high-resolution image segmentation and solve the problem of incomplete segmentation caused by small discrimination of foreground and background in the complex pattern near the edge of the target to be segmented, we propose a fast image segmentation algorithm based on superpixel multi-feature fusion (SMFF). Firstly, the most effective superpixel algorithm is used for superpixel processing, and then the superpixel-based HOG feature, laboratory color feature and spatial position feature are extracted. Lastly, by designing a multi-feature measurement algorithm, the fast image segmentation algorithm based on superpixel multi-feature fusion is implemented. Experimental results verify the effectiveness of the proposed algorithm, which is close to the most classical image segmentation algorithm, and the time performance of the proposed algorithm is significantly better than other comparison algorithms. © 2019, Chinese Institute of Electronics. All right reserved.

引用

页码：2126 / 2133

页数：7

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