基于2维Tsallis熵的水下图像目标检测

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唐旭东, 庞永杰, 张铁栋, 李晔. 基于2维Tsallis熵的水下图像目标检测[J]. 机器人, 2010, 32(3): 289-297.. TANG Xudong, PANG Yongjie, ZHANG Tiedong, LI Ye. Detection of Objects in Underwater Images Based on the Two-Dimensional Tsallis Entropy. ROBOT, 2010, 32(3): 289-297..

摘要针对传统图像检测方法在水下图像处理过程中存在目标区域定位不准确、目标细节丢失、目标形状变形的问题，文中利用Tsallis熵的非广延性，提出了一种基于边缘信息的2维直方图，并以最大2维Tsallis熵为准则，利用改进粒子群优化算法寻找最佳阈值．水下图像处理试验表明，该算法是一种有效的水下图像目标检测方法，与传统方法相比，具有更强的自适应性和鲁棒性．

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	唐旭东
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	李晔

关键词 ：水下图像, Tsallis熵, 目标检测, 改进粒子群优化算法

Abstract：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.

Key words： underwater image Tsallis entropy object detection improved PSO(particle swarm optimization)

收稿日期: 2009-07-12 录用日期: 2009-11-04

TP242

基金资助:国家863计划资助项目（2008AA092301）；国家自然科学基金资助项目（50909025/E091002）；中国博士后科学基金资助项目（20080440838）；黑龙江省博士后基金资助项目；哈尔滨工程大学基础研究基金资助项目（HEUFT08001,HEUFT08017）；水下智能机器人技术国防科技重点实验室开放课题研究基金资助项目（2007001,2008003）

通讯作者: 唐旭东 E-mail: tangxudong@yahoo.cn

作者简介: 唐旭东(1983- )，男，博士生．研究领域：水下机器人智能控制，模式识别，管道跟踪．
庞永杰(1955- )，男，教授，博士生导师．研究领域：水下机器人设计，运动仿真．

链接本文:

https://robot.sia.cn/CN/ 或 https://robot.sia.cn/CN/Y2010/V32/I3/289

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