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基于二维最小Tsallis交叉熵的图像阈值分割方法
  • ISSN号：1000-3290
  • 期刊名称：《物理学报》
  • 时间：0
  • 分类：TP391.41[自动化与计算机技术—计算机应用技术;自动化与计算机技术—计算机科学与技术] P131[天文地球—天体力学;天文地球—天文学]
  • 作者机构：[1]燕山大学工业计算机控制工程河北省重点实验室,秦皇岛066004
  • 相关基金：国家杰出青年基金（批准号：60525303）;燕山大学博士基金（批准号：B243）,燕山大学科技发展基金（批准号：YDJJ200521）资助的课题.
作者： 唐英干[1], 邸秋艳[1], 赵立兴[1], 关新平[1], 刘福才[1]
关键词： Tsallis交叉熵, 二维直方图, 粒子群优化算法, 图像分割, Tsallis-cross entropy,two-dimensional histogram,particle swarm optimization,image segmentation
中文摘要：

利用Tsallis熵的非广延性,提出了二维最小Tsallis交叉熵阈值分割方法.首先给出了二维Tsallis交叉熵的定义,并以最小二维Tsallis交叉熵为准则,利用粒子群优化算法来搜索最优二维阈值向量.该方法不仅进一步考虑了像素之间的空间邻域信息,而且考虑了目标和背景之间的相互关系,其分割性能优于基于Shannon熵的交叉熵阈值法和一维最小Tsallis交叉熵阈值法,并且具有很强的抗噪声能力.实验结果表明,该方法可以实现快速、准确的分割.

英文摘要：

Image thresholding segmentation method based on two-dimensional minimum Tsallis-cross entropy is proposed by utilizing the non-extensive property of Tsallis entropy in the paper.Firstly,the two-dimensional Tsallis-cross entropy is given,then the particle swarm optimization is used to search the best two-dimensional threshold vector by minimizing the two-dimensional Tsallis-cross entropy.The proposed method not only considers the spatial information of pixels,but also the interaction between the object and the background.Its segmentation performance is superior to thresholding methods using Shannon entropy and minimum one-dimensional Tsallis-cross entropy.Experimental results show that the proposed method can give good segmentation results with less computation time.

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期刊信息
  • 《物理学报》
  • 北大核心期刊（2011版）
  • 主管单位:中国科学院
  • 主办单位:中国物理学会 中国科学院物理研究所
  • 主编：欧阳钟灿
  • 地址：北京603信箱(中国科学院物理研究所)
  • 邮编：100190
  • 邮箱：apsoffice@iphy.ac.cn
  • 电话：010-82649026
  • 国际标准刊号：ISSN：1000-3290
  • 国内统一刊号：ISSN：11-1958/O4
  • 邮发代号:2-425
  • 获奖情况:
  • 1999年首届国家期刊奖,2000年中科院优秀期刊特等奖,2001年科技期刊最高方阵队双高期刊居中国期刊第12位
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  • 美国化学文摘（网络版）,荷兰文摘与引文数据库,美国工程索引,美国科学引文索引（扩展库）,英国科学文摘数据库,日本日本科学技术振兴机构数据库,中国中国科技核心期刊,中国北大核心期刊（2004版）,中国北大核心期刊（2008版）,中国北大核心期刊（2011版）,中国北大核心期刊（2014版）,中国北大核心期刊（2000版）
  • 被引量:49876