Detection of objects in underwater images based on the two-dimensional tsallis entropy

被引：0

作者：

Tang X. ^{[1
]}

Pang Y. ^{[1
]}

Zhang T. ^{[1
]}

Li Y. ^{[1
]}

机构：

[1] National Key Laboratory of Science and Technology on Autonomous Underwater Vehicle, Harbin Engineering University

来源：

Jiqiren/Robot | 2010年 / 32卷 / 03期

关键词：

Improved PSO (particle swarm optimization); Object detection; Tsallis entropy; Underwater image;

D O I：

10.3724/SP.J.1218.2010.00289

中图分类号：

学科分类号：

摘要：

For the problems in underwater image processing by traditional image detection methods, such as inaccurate location of objects regions, loss of object details and distortion of object shape, etc., a new two-dimensional histogram based on edge information is proposed by utilizing the non-extensive property of Tsallis entropy. The improved particle swarm optimization (PSO) is used to search the best threshold value by maximizing the two-dimensional Tsallis entropy. The test results of some underwater images show that it is efficient to detect objects in underwater images. Comparing with traditional methods, the proposed approach shows better adaptability and robustness.

引用

页码：289 / 297

页数：8

共 13 条

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[12] Otsu N., A threshold selection method from gray-level histograms, IEEE Transactions on Systems, Man, and Cybernetics, 9, 1, pp. 62-66, (1979)
[13] Sahoo P.K., Arora G., Image thresholding using two-dimensional Tsallis-Havrda-Charvat entropy, Pattern Recognition Letters, 27, 6, pp. 520-528, (2006)

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