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Image segmentation by combining the global and local properties
Wang ZZ(王振洲)
Department机器人学研究室
Source PublicationExpert Systems with Applications
ISSN0957-4174
2017
Volume87Pages:30-40
Indexed BySCI ; EI
EI Accession number20172403764750
WOS IDWOS:000407183900003
Contribution Rank1
Funding OrganizationChinese Academy of Sciences for the funding with the grant number Y5A1270101.
KeywordSegmentation Histogram Gibbs Distribution Slope Difference Distribution
AbstractImage segmentation plays a fundamental role in many computer vision applications. It is challenging because of the vast variety of images involved and the diverse segmentation requirements in different applications. As a result, it remains an open problem after so many years of study by researchers all over the world. In this paper, we propose to segment the image by combing its global and local properties. The global properties of the image are characterized by the mean values of different pixel classes and the continuous boundary of the object or region. The local properties are characterized by the interactions of neighboring pixels and the image edge. The proposed approach consists of four basic parts corresponding to the global or local property of the image respectively: (1) The slope difference distribution that is used to compute the global mean values of different pixel classes; (2) Energy minimization to remove inhomogeneity based on Gibbs distribution that complies with local interactions of neighboring pixels; (3) The Canny operator that is used to detect the local edge of the object or the region; (4) The polynomial spline that is used to smooth the boundary of the object or the region. These four basic parts are applied one by one and each of them is indispensable for the achieved high accuracy. A large variety of images are used to validate the proposed approach and the results are favorable.
Language英语
WOS HeadingsScience & Technology ; Technology
WOS SubjectComputer Science, Artificial Intelligence ; Engineering, Electrical & Electronic ; Operations Research & Management Science
WOS KeywordNOISE ESTIMATION ; ACTIVE CONTOURS ; RANDOM-FIELDS ; ALGORITHMS ; CUTS
WOS Research AreaComputer Science ; Engineering ; Operations Research & Management Science
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Document Type期刊论文
Identifierhttp://ir.sia.cn/handle/173321/20754
Collection机器人学研究室
Corresponding AuthorWang ZZ(王振洲)
AffiliationState Key Lab of Robotics, Shenyang Institute of Automation, Chinese Academy of Science (CAS), Shenyang, China
Recommended Citation
GB/T 7714
Wang ZZ. Image segmentation by combining the global and local properties[J]. Expert Systems with Applications,2017,87:30-40.
APA Wang ZZ.(2017).Image segmentation by combining the global and local properties.Expert Systems with Applications,87,30-40.
MLA Wang ZZ."Image segmentation by combining the global and local properties".Expert Systems with Applications 87(2017):30-40.
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