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A flexible and robust threshold selection method
Wang ZZ(王振洲); Xiong JJ(熊晶晶); Yang YM(杨永明); Li HX(李海星)
作者部门机器人学研究室
关键词Threshold Selection Clustering Image Segmentation Slope Difference Distribution
发表期刊IEEE Transactions on Circuits and Systems for Video Technology
ISSN1051-8215
2018
卷号28期号:9页码:2220-2232
收录类别SCI ; EI
EI收录号20172903957194
WOS记录号WOS:000444843100013
产权排序1
资助机构Chinese Academy of Sciences
摘要

Despite the great prosperity and fast development of image segmentation technology, threshold selection method is still the best choice in many practical applications. State of the art threshold selection methods perform poorly in segmenting many images with different modalities, e.g. the magnetic resonance (MR) images, cell images and laser line images. Thus, it is desirable to come up with a more robust method that could segment images with different modalities with the optimum accuracy. To this end, the method should be flexible and its parameters should be adjustable for different types of images. In this paper, we propose to compute the threshold based on the slope difference distribution which is computed from the image histogram with adjustable parameters. Firstly, the pixels are clustered based on the peaks of the slope difference distribution into different pixel classes. Secondly, the threshold is selected based on the valleys of the slope difference distribution to separate the pixel classes. The robustness of this threshold selection method relies on the adjustable parameters that could be calibrated to achieve the optimum segmentation accuracy for each specific type of images. The proposed threshold selection method is tested on both the synthesized images and the real images. Experimental results show that the proposed method outperforms state of the art methods as a whole.

语种英语
WOS类目Engineering, Electrical & Electronic
关键词[WOS]MEANS CLUSTERING-ALGORITHM ; IMAGE SEGMENTATION ; MAXIMUM-LIKELIHOOD ; ACTIVE CONTOURS ; CRITERION ; DISTANCE ; MODELS ; LINES
WOS研究方向Engineering
资助项目Chinese Academy of Sciences[Y5A1270101]
引用统计
文献类型期刊论文
条目标识符http://ir.sia.cn/handle/173321/20805
专题机器人学研究室
通讯作者Wang ZZ(王振洲)
作者单位State Key Laboratory of Robotics at Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang City, 110016, China
推荐引用方式
GB/T 7714
Wang ZZ,Xiong JJ,Yang YM,et al. A flexible and robust threshold selection method[J]. IEEE Transactions on Circuits and Systems for Video Technology,2018,28(9):2220-2232.
APA Wang ZZ,Xiong JJ,Yang YM,&Li HX.(2018).A flexible and robust threshold selection method.IEEE Transactions on Circuits and Systems for Video Technology,28(9),2220-2232.
MLA Wang ZZ,et al."A flexible and robust threshold selection method".IEEE Transactions on Circuits and Systems for Video Technology 28.9(2018):2220-2232.
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