A Sonar Image Segmentation Algorithm based on Two-Dimensional Spatio-Temporal Fuzzy Entropy

被引：0

作者：

Lu Zhen ^{[1
]}

Chen Yuchao ^{[1
]}

Zhang Tiedong ^{[2
]}

Yu Jun ^{[1
]}

机构：

[1] China Ship Sci Res Ctr, Wuxi, Jiangsu, Peoples R China

[2] Harbin Engn Univ, Harbin, Peoples R China

来源：

2018 IEEE 8TH INTERNATIONAL CONFERENCE ON UNDERWATER SYSTEM TECHNOLOGY: THEORY AND APPLICATIONS (USYS) | 2018年

关键词：

sonar image; image segmentation; two-dimensional entropy; fuzzy theory; frame difference;

D O I：

暂无

中图分类号：

U6 [水路运输]; P75 [海洋工程];

学科分类号：

0814 ; 081505 ; 0824 ; 082401 ;

摘要：

Firstly, this article introduces a two-dimensional fuzzy entropy threshold segmentation method, taking characteristics of underwater sonar image of moving target into account, the concept of time in the traditional frame difference motion detection method is used. To determine the grayscale image segmentation threshold, a two-dimensional spatiotemporal fuzzy entropy algorithm is established. The algorithm is used in forward-looking sonar image threshold segmentation to verify the applicability and good performance. Compared to other threshold algorithms, the algorithm of this article can obtain better segmentation threshold value and have more advantages in the processing of sonar image which contains more noise.

引用

页数：5

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