Show simple item record

Detection of diffuse and specular interface reflections and inter-reflections by color image segmentation

dc.contributor.authorBajcsy, Ruzenaen_US
dc.contributor.authorLee, Sang Wooken_US
dc.contributor.authorLeonardis, Alešen_US
dc.date.accessioned2006-09-08T19:06:44Z
dc.date.available2006-09-08T19:06:44Z
dc.date.issued1996-03en_US
dc.identifier.citationBajcsy, Ruzena; Lee, Sang Wook; Leonardis, Aleš; (1996). "Detection of diffuse and specular interface reflections and inter-reflections by color image segmentation." International Journal of Computer Vision 17(3): 241-272. <http://hdl.handle.net/2027.42/41303>en_US
dc.identifier.issn0920-5691en_US
dc.identifier.issn1573-1405en_US
dc.identifier.urihttps://hdl.handle.net/2027.42/41303
dc.description.abstractWe present a computational model and algorithm for detecting diffuse and specular interface reflections and some inter-reflections. Our color reflection model is based on the dichromatic model for dielectric materials and on a color space, called S space, formed with three orthogonal basis functions. We transform color pixels measured in RGB into the S space and analyze color variations on objects in terms of brightness, hue and saturation which are defined in the S space. When transforming the original RGB data into the S space, we discount the scene illumination color that is estimated using a white reference plate as an active probe. As a result, the color image appears as if the scene illumination is white. Under the whitened illumination, the interface reflection clusters in the S space are all aligned with the brightness direction. The brightness, hue and saturation values exhibit a more direct correspondence to body colors and to diffuse and specular interface reflections, shading, shadows and inter-reflections than the RGB coordinates. We exploit these relationships to segment the color image, and to separate specular and diffuse interface reflections and some inter-reflections from body reflections. The proposed algorithm is effications for uniformly colored dielectric surfaces under singly colored scene illumination. Experimental results conform to our model and algorithm within the liminations discussed.en_US
dc.format.extent2535704 bytes
dc.format.extent3115 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypetext/plain
dc.language.isoen_US
dc.publisherKluwer Academic Publishers; Springer Science+Business Mediaen_US
dc.subject.otherComputer Scienceen_US
dc.subject.otherArtificial Intelligence (Incl. Robotics)en_US
dc.subject.otherComputer Imaging, Graphics and Computer Visionen_US
dc.subject.otherImage Processingen_US
dc.subject.otherAutomation and Roboticsen_US
dc.titleDetection of diffuse and specular interface reflections and inter-reflections by color image segmentationen_US
dc.typeArticleen_US
dc.subject.hlbsecondlevelComputer Scienceen_US
dc.subject.hlbtoplevelEngineeringen_US
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationumDept. of Electrical Engineering and Computer Science, Univ. of Michigan, 1101 Beal Ave., 48109, Ann Arbor, MIen_US
dc.contributor.affiliationotherGRASP Laboratory, Department of Computer and Information Science, University of Pennsylvania, 19104, Philadelphia, PAen_US
dc.contributor.affiliationotherFaculty of Electrical Engineering and Computer Science, Trzaska c. 25, 61001, Ljubljana, Sloveniaen_US
dc.contributor.affiliationumcampusAnn Arboren_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/41303/1/11263_2004_Article_BF00128233.pdfen_US
dc.identifier.doihttp://dx.doi.org/10.1007/BF00128233en_US
dc.identifier.sourceInternational Journal of Computer Visionen_US
dc.owningcollnameInterdisciplinary and Peer-Reviewed


Files in this item

Show simple item record

Remediation of Harmful Language

The University of Michigan Library aims to describe library materials in a way that respects the people and communities who create, use, and are represented in our collections. Report harmful or offensive language in catalog records, finding aids, or elsewhere in our collections anonymously through our metadata feedback form. More information at Remediation of Harmful Language.

Accessibility

If you are unable to use this file in its current format, please select the Contact Us link and we can modify it to make it more accessible to you.