Thresholding approaches with interval-valued fuzzy sets to image segmentation
Thresholding approaches are fundamental and important techniques in image segmentation. There exist lots of integrated techniques of thresholding methods with fuzzy sets theory. The fuzzy compactness and fuzzy divergence are powerful tools in dealing with vague and imprecise data, and are widely app...
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| creator | Tingquan Deng Peipei Wang Yuling Mei Wenjie Liu |
| description | Thresholding approaches are fundamental and important techniques in image segmentation. There exist lots of integrated techniques of thresholding methods with fuzzy sets theory. The fuzzy compactness and fuzzy divergence are powerful tools in dealing with vague and imprecise data, and are widely applied to thresholding segmentation for images. This paper extends the two kinds of fuzzy measures to interval-valued fuzzy sets to eliminate uncertain assignments of membership degrees of pixels in images. Two thresholding techniques are proposed for image segmentation. The affinity characteristics of pixels in images are sufficiently considered in the new techniques. The experimental results show that the selection of initial membership functions brings little impact on thresholding segmentation of images. |
| doi_str_mv | 10.1109/ISKE.2008.4731086 |
| format | Conference Proceeding |
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There exist lots of integrated techniques of thresholding methods with fuzzy sets theory. The fuzzy compactness and fuzzy divergence are powerful tools in dealing with vague and imprecise data, and are widely applied to thresholding segmentation for images. This paper extends the two kinds of fuzzy measures to interval-valued fuzzy sets to eliminate uncertain assignments of membership degrees of pixels in images. Two thresholding techniques are proposed for image segmentation. The affinity characteristics of pixels in images are sufficiently considered in the new techniques. 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There exist lots of integrated techniques of thresholding methods with fuzzy sets theory. The fuzzy compactness and fuzzy divergence are powerful tools in dealing with vague and imprecise data, and are widely applied to thresholding segmentation for images. This paper extends the two kinds of fuzzy measures to interval-valued fuzzy sets to eliminate uncertain assignments of membership degrees of pixels in images. Two thresholding techniques are proposed for image segmentation. The affinity characteristics of pixels in images are sufficiently considered in the new techniques. The experimental results show that the selection of initial membership functions brings little impact on thresholding segmentation of images.</description><subject>Educational institutions</subject><subject>Fuzzy set theory</subject><subject>Fuzzy sets</subject><subject>Image analysis</subject><subject>Image segmentation</subject><subject>Intelligent systems</subject><subject>Knowledge engineering</subject><subject>Pixel</subject><subject>Power engineering and energy</subject><subject>Robustness</subject><isbn>9781424421961</isbn><isbn>1424421969</isbn><isbn>1424421977</isbn><isbn>9781424421978</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2008</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNo1UNFKwzAUjchAN_sB4kt-oDU3SZvkUcbU4cQH5_NI27s20rWjyZTt6404D1wu53C5nHMIuQWWATBzv3x_WWScMZ1JJYDp4oJMQXIpORilLklilP7nBUzI9PfWMOAarkji_SeLECaX0lyT13U7om-HrnZ9Q-1-Pw62atHTbxda6vqA45ft0jgHrOn2cDodqcfgaRio29kGI2t22Acb3NDfkMnWdh6T856Rj8fFev6crt6elvOHVepA5SGtdYW8MIYjZ4LLymquVV1YlRcWVJlL5KpAA4Jx1DWPmiwxRpcSZBmjiBm5-_vrEHGzH6OT8bg51yF-ADxUUSY</recordid><startdate>200811</startdate><enddate>200811</enddate><creator>Tingquan Deng</creator><creator>Peipei Wang</creator><creator>Yuling Mei</creator><creator>Wenjie Liu</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>200811</creationdate><title>Thresholding approaches with interval-valued fuzzy sets to image segmentation</title><author>Tingquan Deng ; Peipei Wang ; Yuling Mei ; Wenjie Liu</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i175t-d8ce26992e20324ca8287d6a756a17b54e276e91302e8d2a174be1094414b8903</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2008</creationdate><topic>Educational institutions</topic><topic>Fuzzy set theory</topic><topic>Fuzzy sets</topic><topic>Image analysis</topic><topic>Image segmentation</topic><topic>Intelligent systems</topic><topic>Knowledge engineering</topic><topic>Pixel</topic><topic>Power engineering and energy</topic><topic>Robustness</topic><toplevel>online_resources</toplevel><creatorcontrib>Tingquan Deng</creatorcontrib><creatorcontrib>Peipei Wang</creatorcontrib><creatorcontrib>Yuling Mei</creatorcontrib><creatorcontrib>Wenjie Liu</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Tingquan Deng</au><au>Peipei Wang</au><au>Yuling Mei</au><au>Wenjie Liu</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Thresholding approaches with interval-valued fuzzy sets to image segmentation</atitle><btitle>2008 3rd International Conference on Intelligent System and Knowledge Engineering</btitle><stitle>ISKE</stitle><date>2008-11</date><risdate>2008</risdate><volume>1</volume><spage>1059</spage><epage>1064</epage><pages>1059-1064</pages><isbn>9781424421961</isbn><isbn>1424421969</isbn><eisbn>1424421977</eisbn><eisbn>9781424421978</eisbn><abstract>Thresholding approaches are fundamental and important techniques in image segmentation. There exist lots of integrated techniques of thresholding methods with fuzzy sets theory. The fuzzy compactness and fuzzy divergence are powerful tools in dealing with vague and imprecise data, and are widely applied to thresholding segmentation for images. This paper extends the two kinds of fuzzy measures to interval-valued fuzzy sets to eliminate uncertain assignments of membership degrees of pixels in images. Two thresholding techniques are proposed for image segmentation. The affinity characteristics of pixels in images are sufficiently considered in the new techniques. The experimental results show that the selection of initial membership functions brings little impact on thresholding segmentation of images.</abstract><pub>IEEE</pub><doi>10.1109/ISKE.2008.4731086</doi><tpages>6</tpages></addata></record> |
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| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Educational institutions Fuzzy set theory Fuzzy sets Image analysis Image segmentation Intelligent systems Knowledge engineering Pixel Power engineering and energy Robustness |
| title | Thresholding approaches with interval-valued fuzzy sets to image segmentation |
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