Efficient Skin Region Segmentation Using Low Complexity Fuzzy Decision Tree Model
We propose an efficient skin region segmentation methodology using low complexity fuzzy decision tree constructed over B, G, R colour space. Skin and nonskin training dataset has been generated by using various skin textures obtained from face images of diversity of age, gender, and race people and...
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| creator | Bhatt, R.B. Dhall, A. Sharma, G. Chaudhury, S. |
| description | We propose an efficient skin region segmentation methodology using low complexity fuzzy decision tree constructed over B, G, R colour space. Skin and nonskin training dataset has been generated by using various skin textures obtained from face images of diversity of age, gender, and race people and nonskin pixels obtained from arbitrary thousands of random sampling of nonskin textures. Compact fuzzy model with very few numbers of rules allow to raster scan consumer photographs and classify each pixel as skin or nonskin for various face and human detection applications for embedded platforms. |
| doi_str_mv | 10.1109/INDCON.2009.5409447 |
| format | Conference Proceeding |
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Skin and nonskin training dataset has been generated by using various skin textures obtained from face images of diversity of age, gender, and race people and nonskin pixels obtained from arbitrary thousands of random sampling of nonskin textures. Compact fuzzy model with very few numbers of rules allow to raster scan consumer photographs and classify each pixel as skin or nonskin for various face and human detection applications for embedded platforms.</description><subject>Classification tree analysis</subject><subject>Decision trees</subject><subject>Embedded system</subject><subject>Face detection</subject><subject>Humans</subject><subject>Image databases</subject><subject>Image sampling</subject><subject>Image segmentation</subject><subject>Induction generators</subject><subject>Skin</subject><issn>2325-940X</issn><isbn>1424448581</isbn><isbn>9781424448586</isbn><isbn>142444859X</isbn><isbn>9781424448593</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2009</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNpFkEFPwkAUhNcoiYD8Ai77B4r7dt-23aMpoCQVokDCjWzbt2QVWkIxWn69EEk8Tb7JzByGsT6IAYAwj5PpMJlNB1IIM9AoDGJ0wzqAEhFjbVa3_xDDHWtLJXVgUKxarHMpGaFDDfesV9cfQoizBaCxzd5GzvncU3nk809f8nfa-Krkc9rszp49XmBZ-3LD0-qbJ9Vuv6Uff2z4-Ot0aviQcl9fMosDEX-tCto-sJaz25p6V-2y5Xi0SF6CdPY8SZ7SwIPSUQDSaTQ2xDAkVyjUuY4sWpkXhcoMAWSRsTbKbUEuJ6VjqUUGlDks0FkRqS7r_-16IlrvD35nD836-o36BZz9VT0</recordid><startdate>200912</startdate><enddate>200912</enddate><creator>Bhatt, R.B.</creator><creator>Dhall, A.</creator><creator>Sharma, G.</creator><creator>Chaudhury, S.</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>200912</creationdate><title>Efficient Skin Region Segmentation Using Low Complexity Fuzzy Decision Tree Model</title><author>Bhatt, R.B. ; Dhall, A. ; Sharma, G. ; Chaudhury, S.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i1357-12f549a6466efd345c57a4a2cdd3b9e11b79aa7cadefce358250b1ebf4d4fa073</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2009</creationdate><topic>Classification tree analysis</topic><topic>Decision trees</topic><topic>Embedded system</topic><topic>Face detection</topic><topic>Humans</topic><topic>Image databases</topic><topic>Image sampling</topic><topic>Image segmentation</topic><topic>Induction generators</topic><topic>Skin</topic><toplevel>online_resources</toplevel><creatorcontrib>Bhatt, R.B.</creatorcontrib><creatorcontrib>Dhall, A.</creatorcontrib><creatorcontrib>Sharma, G.</creatorcontrib><creatorcontrib>Chaudhury, S.</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 Xplore (Online service)</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>Bhatt, R.B.</au><au>Dhall, A.</au><au>Sharma, G.</au><au>Chaudhury, S.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Efficient Skin Region Segmentation Using Low Complexity Fuzzy Decision Tree Model</atitle><btitle>2009 Annual IEEE India Conference</btitle><stitle>INDCON</stitle><date>2009-12</date><risdate>2009</risdate><spage>1</spage><epage>4</epage><pages>1-4</pages><issn>2325-940X</issn><isbn>1424448581</isbn><isbn>9781424448586</isbn><eisbn>142444859X</eisbn><eisbn>9781424448593</eisbn><abstract>We propose an efficient skin region segmentation methodology using low complexity fuzzy decision tree constructed over B, G, R colour space. Skin and nonskin training dataset has been generated by using various skin textures obtained from face images of diversity of age, gender, and race people and nonskin pixels obtained from arbitrary thousands of random sampling of nonskin textures. Compact fuzzy model with very few numbers of rules allow to raster scan consumer photographs and classify each pixel as skin or nonskin for various face and human detection applications for embedded platforms.</abstract><pub>IEEE</pub><doi>10.1109/INDCON.2009.5409447</doi><tpages>4</tpages><oa>free_for_read</oa></addata></record> |
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| ispartof | 2009 Annual IEEE India Conference, 2009, p.1-4 |
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| language | eng |
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| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Classification tree analysis Decision trees Embedded system Face detection Humans Image databases Image sampling Image segmentation Induction generators Skin |
| title | Efficient Skin Region Segmentation Using Low Complexity Fuzzy Decision Tree Model |
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