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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)
Department机器人学研究室
Source PublicationIEEE Transactions on Circuits and Systems for Video Technology
ISSN1051-8215
2018
Volume28Issue:9Pages:2220-2232
Indexed BySCI ; EI
EI Accession number20172903957194
WOS IDWOS:000444843100013
Contribution Rank1
Funding OrganizationChinese Academy of Sciences
KeywordThreshold Selection Clustering Image Segmentation Slope Difference Distribution
Abstract

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.

Language英语
WOS SubjectEngineering, Electrical & Electronic
WOS KeywordMEANS CLUSTERING-ALGORITHM ; IMAGE SEGMENTATION ; MAXIMUM-LIKELIHOOD ; ACTIVE CONTOURS ; CRITERION ; DISTANCE ; MODELS ; LINES
WOS Research AreaEngineering
Funding ProjectChinese Academy of Sciences[Y5A1270101]
Citation statistics
Cited Times:4[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.sia.cn/handle/173321/20805
Collection机器人学研究室
Corresponding AuthorWang ZZ(王振洲)
AffiliationState Key Laboratory of Robotics at Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang City, 110016, China
Recommended Citation
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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