Estimation of illuminant chromaticity based on highlight detection for face images with varying illumination
Illuminant chromaticity estimation is required in the fields of the tracking and recognition of human faces, compensation and detection of skin color, image reproduction, and color constancy. This article proposes a simple and effective method to estimate the illuminant chromaticity using highlights...
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Veröffentlicht in: | Color research and application 2014-04, Vol.39 (2), p.188-199 |
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description | Illuminant chromaticity estimation is required in the fields of the tracking and recognition of human faces, compensation and detection of skin color, image reproduction, and color constancy. This article proposes a simple and effective method to estimate the illuminant chromaticity using highlights from the face region. We first select the candidate points through the detection of highlights around the leftmost pixel of the rg chromaticity space from the facial images under various illuminant conditions and then estimate the illuminant chromaticity by averaging the chromaticities of the candidate points. To enhance the illuminant chromaticity estimation accuracy, we propose a more elaborate estimation method, which effectively readjusts the candidate points of the highlight regions according to the conditions derived from two ethnic and three illuminant groups. The experiment results show that our proposed method reliably estimates the illuminant chromaticity under various color temperatures and illuminant directions. © 2012 Wiley Periodicals, Inc. Col Res Appl, 39, 188–199, 2014 |
doi_str_mv | 10.1002/col.21772 |
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This article proposes a simple and effective method to estimate the illuminant chromaticity using highlights from the face region. We first select the candidate points through the detection of highlights around the leftmost pixel of the rg chromaticity space from the facial images under various illuminant conditions and then estimate the illuminant chromaticity by averaging the chromaticities of the candidate points. To enhance the illuminant chromaticity estimation accuracy, we propose a more elaborate estimation method, which effectively readjusts the candidate points of the highlight regions according to the conditions derived from two ethnic and three illuminant groups. The experiment results show that our proposed method reliably estimates the illuminant chromaticity under various color temperatures and illuminant directions. © 2012 Wiley Periodicals, Inc. 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Appl</addtitle><description>Illuminant chromaticity estimation is required in the fields of the tracking and recognition of human faces, compensation and detection of skin color, image reproduction, and color constancy. This article proposes a simple and effective method to estimate the illuminant chromaticity using highlights from the face region. We first select the candidate points through the detection of highlights around the leftmost pixel of the rg chromaticity space from the facial images under various illuminant conditions and then estimate the illuminant chromaticity by averaging the chromaticities of the candidate points. To enhance the illuminant chromaticity estimation accuracy, we propose a more elaborate estimation method, which effectively readjusts the candidate points of the highlight regions according to the conditions derived from two ethnic and three illuminant groups. The experiment results show that our proposed method reliably estimates the illuminant chromaticity under various color temperatures and illuminant directions. © 2012 Wiley Periodicals, Inc. Col Res Appl, 39, 188–199, 2014</description><subject>Chromaticity</subject><subject>correlated color temperature</subject><subject>highlight detection</subject><subject>illuminant chromaticity estimation</subject><subject>illuminant color</subject><issn>0361-2317</issn><issn>1520-6378</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2014</creationdate><recordtype>article</recordtype><recordid>eNp1kE1PwkAQhjdGExE9-A_2qIfCfrTd9mhQQUMkMRgTL5vtdgqrS4u7i8i_t4By8zCZwzzPm8yL0CUlPUoI6-vG9hgVgh2hDk0YiVIusmPUITylEeNUnKIz798JIQnPRAfZOx_MQgXT1LipsLF2tTC1qgPWc9dsD9qEDS6UhxK3zNzM5radgEsIoHde1ThcKQ24DZqBx2sT5vhLuY2pZ4fELXmOTiplPVz87i56ub-bDkbReDJ8GNyMI83bH6JK5arMy6TISoBYgxaZrgouYpISXiY0FlylrFBVGrOE85xmCeF5XAKjtCg08C662ucuXfO5Ah_kwngN1qoampWXNM5jzvI0yVr0eo9q13jvoJJL177hNpISuW1Uto3KXaMt29-za2Nh8z8oB5PxnxHtDeMDfB8M5T5kKrhI5OvTUGaPw-nzmxjJW_4DSpaJRw</recordid><startdate>201404</startdate><enddate>201404</enddate><creator>Kwon, Oh-Yeol</creator><creator>Chien, Sung-Il</creator><general>Blackwell Publishing Ltd</general><scope>BSCLL</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7U5</scope><scope>8FD</scope><scope>L7M</scope></search><sort><creationdate>201404</creationdate><title>Estimation of illuminant chromaticity based on highlight detection for face images with varying illumination</title><author>Kwon, Oh-Yeol ; Chien, Sung-Il</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3002-fa9ad9d5b8dee4cec78cfb3740603d51473a62baf64253391850394de211bbce3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2014</creationdate><topic>Chromaticity</topic><topic>correlated color temperature</topic><topic>highlight detection</topic><topic>illuminant chromaticity estimation</topic><topic>illuminant color</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Kwon, Oh-Yeol</creatorcontrib><creatorcontrib>Chien, Sung-Il</creatorcontrib><collection>Istex</collection><collection>CrossRef</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>Technology Research Database</collection><collection>Advanced Technologies Database with Aerospace</collection><jtitle>Color research and application</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Kwon, Oh-Yeol</au><au>Chien, Sung-Il</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Estimation of illuminant chromaticity based on highlight detection for face images with varying illumination</atitle><jtitle>Color research and application</jtitle><addtitle>Color Res. Appl</addtitle><date>2014-04</date><risdate>2014</risdate><volume>39</volume><issue>2</issue><spage>188</spage><epage>199</epage><pages>188-199</pages><issn>0361-2317</issn><eissn>1520-6378</eissn><abstract>Illuminant chromaticity estimation is required in the fields of the tracking and recognition of human faces, compensation and detection of skin color, image reproduction, and color constancy. This article proposes a simple and effective method to estimate the illuminant chromaticity using highlights from the face region. We first select the candidate points through the detection of highlights around the leftmost pixel of the rg chromaticity space from the facial images under various illuminant conditions and then estimate the illuminant chromaticity by averaging the chromaticities of the candidate points. To enhance the illuminant chromaticity estimation accuracy, we propose a more elaborate estimation method, which effectively readjusts the candidate points of the highlight regions according to the conditions derived from two ethnic and three illuminant groups. The experiment results show that our proposed method reliably estimates the illuminant chromaticity under various color temperatures and illuminant directions. © 2012 Wiley Periodicals, Inc. Col Res Appl, 39, 188–199, 2014</abstract><pub>Blackwell Publishing Ltd</pub><doi>10.1002/col.21772</doi><tpages>12</tpages></addata></record> |
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subjects | Chromaticity correlated color temperature highlight detection illuminant chromaticity estimation illuminant color |
title | Estimation of illuminant chromaticity based on highlight detection for face images with varying illumination |
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