Full metadata record
DC FieldValueLanguage
dc.contributor.authorChen, HCen_US
dc.contributor.authorChien, WJen_US
dc.contributor.authorWang, SJen_US
dc.date.accessioned2014-12-08T15:38:54Z-
dc.date.available2014-12-08T15:38:54Z-
dc.date.issued2004-07-01en_US
dc.identifier.issn1070-9908en_US
dc.identifier.urihttp://dx.doi.org/10.1109/LSP.2004.830116en_US
dc.identifier.urihttp://hdl.handle.net/11536/26638-
dc.description.abstractIn this letter, we propose a color image segmentation algorithm based on contrast information. Given a color image, we use contrast information, instead of the commonly used derivative information, to detect edges. To fit for human's visual perception, the CIE L*a*b* color space is used and the DeltaE(ab) color difference is adopted as the measure of color contrast. A subjective experiment is made to demonstrate the weak correlation between the perceived color contrast and the levels of (L*, a*, b*). This experiment implies the feasibility of using a single-threshold scheme to suppress perceptually, faint boundaries. A complete segmentation scheme is proposed and the simulation results demonstrate the superiority of this approach in providing reasonable and reliable color image segmentation.en_US
dc.language.isoen_USen_US
dc.subjectCIE L*a*b* color spaceen_US
dc.subjectcolor differenceen_US
dc.subjectcolor image segmentationen_US
dc.subjectcontrasten_US
dc.titleContrast-based color image segmentationen_US
dc.typeArticleen_US
dc.identifier.doi10.1109/LSP.2004.830116en_US
dc.identifier.journalIEEE SIGNAL PROCESSING LETTERSen_US
dc.citation.volume11en_US
dc.citation.issue7en_US
dc.citation.spage641en_US
dc.citation.epage644en_US
dc.contributor.department電子工程學系及電子研究所zh_TW
dc.contributor.departmentDepartment of Electronics Engineering and Institute of Electronicsen_US
dc.identifier.wosnumberWOS:000222105300014-
dc.citation.woscount17-
Appears in Collections:Articles


Files in This Item:

  1. 000222105300014.pdf

If it is a zip file, please download the file and unzip it, then open index.html in a browser to view the full text content.