Abstract
We 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.
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Bajcsy, R., Lee, S.W., and Leonardis, A. 1989. Computational aspects of color constancy, Technical Report, University of Pennsylvania, Philadelphia, PA.
Bajcsy, R., Lee, S.W., and Leonardis, A. 1990. Color image segmentation with detection of highlights and local illumination induced by inter-reflections. In Proc. 10th International Conf. on Pattern Recognition. Atlantic City, NJ.
Beck, J. 1967. Surface Color Perception. Cornell University Press: Ithaca, NY.
Beckman, P. and Spizzichino, A. 1963. Scattering of Electromagnetic Waves from Rough Surfaces. Pergamon Press: London, UK.
Blake, A. 1985. Specular stereo. In Proc. of 9th Int. Joint Conf. Artif. Intell., Los Angeles, CA, pp. 973–976.
Brelstaff, G. and Blake, A. 1988. Detecting specular reflections using lambertain constraints. In Proc. of IEEE Int. Conf. on Computer Vision, Tarpon Springs, FL, pp.297–302.
Buchsbaum, G. 1980. A spatial processor model for object colour perception. J. Franklin Inst., 310:1–26.
Cohen, J. 1964. Dependency of the spectral reflectance curves of the munsell color chips. Psychon. Sci., 1:369–370.
Coleman, E.N. and Jain, R. 1982. Obtaining 3-dimensional shape of textured and specular surface using four-source photometry. Computer Graphics and Image Processing, 18:308–328.
D'Zmura, M. and Lennie, P. 1986. Mechanisms of color constancy. Journal of the Optical Society of America, 3:1662–1672.
Forsyth, D.A. 1988. A novel approach to colour constancy. Proceedings ICCV, 2:9–18.
Funka-Lea, G. and Bajcsy, R. 1993. Active color image analysis for recognizing shadows. In Proceedings of IJCAI-93, France.
Funt, B.V. and Drew, M.S. 1991. Color space analysis of mutual illumination. Technical report, Simon Fraser University, Burnaby, B.C., Canada.
Gershon, R. 1987. The Use of Color in Computational Vision. Ph.D. thesis, Department of Computer Science, University of Toronto.
Hanson, A.R. and Riseman, E.M. 1978. Segmentation for Natural Scenes. Academic Press: New York, NY.
Healey, G.H. 1989. Using color for geometry-insensitive segmentation. Journal of the Optical Society of America A, 6.
Healey, G.H. and Binford, T.O. 1988a. A color metric for computer vision. In Proceedings of CVPR, New York, NY, pp. 10–17.
Healey, G.H. and Binford, T.O. 1988b. Local shape from specularity. Computer Vision Graphics and Image Processing, 42.
Horn, B.K.P. 1986. Robot Vision. The MIT Press: Boston, MA.
Jepson, A.D., Gershon, R., and Tsotsos, J.K. 1986. Ambient illumination and the determination of material changes. Journal of the Optical Society of America A, 3(10):1700–1707.
Judd, D.B., MacAdam, D.L., and Wyszecki, G.W. 1964. Spectral distribution of typical daylight as a function of correlated color temperature. Journal of the Optical Society of America, 54.
Kanade, T. and Ikeuchi, K. 1991. Introduction to the special issue on physical modeling in computer vision. IEEE Trans. PAMI, 13:609–610.
Lee, H.-C. 1986. Method for computing the scene-illuminant chromaticity from specular highlights. Journal of the Optical Society of America, 3:1694–1699.
Lee, H.-C., Breneman, E.J., and Schulte, C.P. 1990. Modeling light reflection of computer vision. IEEE Trans. PAMI, 12:402–409.
Lee, S.W. 1991. Understanding of Surface Reflections in Computer Vision by Color and Multiple Views. Ph.D. thesis, University of Pennsylvania.
Lee, S.W. and Bajcsy, R. 1992. Detection of specularity using color and multiple views. Image and Vision Computing, 10:643–653.
Leonardis, A., Gupta, A., and Bajcsy, R. 1990. Segmentation as the search for the best description of the image in terms of primitives. In IEEE Proceedings of the Third International Conference on Computer Vision, Osaka, Japan, pp. 121–125.
Maloney, L.T. 1985. Computational approaches to color constancy. Technical report, Applied Psychology Laboratory, Stanford University, Stanford, CA.
Maloney, L.T. 1986. Evaluation of linear models of surface reflectance with small number of parameters. Journal of the Optical Society of America, 3:29–33.
Maloney, L.T. and Wandell, B.A. 1986. A computational model of color constancy. Journal of the Optical Society of America, 1:29–33.
Nassau, K. 1983. The Physics and Chemistry of Color. John Wiley and Sons: New York, NY.
Nayar, S.K., Fang, X.S., and Boult, T. 1993. Separation of reflection components using color and polarization. In Proceedings of the DARPA Image Understanding Workshop, Washington, DC, pp. 1049–1060.
Nayar, S.K., Ikeuchi, K., and Kanade, T. 1990a. Determining shape and reflectance of hybrid surfaces by photometric sampling. IEEE Trans. Robo. Autom., 6:418–431.
Nayar, S.K., Ikeuchi, K., and Kanade, T. 1990b. Shape form inter-reflections. In Proceedings of ICCV, Osaka, Japan, pp. 2–11.
Nayar, S.K., Ikeuchi, K., and Kanade, T. 1991. Surface reflection: Physical and geometrical perspective. IEEE Trans. PAMI, 13:611–634.
Novak, C.L. and Shafer, S.A. 1990. Supervised color constancy using a color chart. Technical report, Carnegie Mellon University, Pittsburgh, PA.
Novak, C.L. and Shafer, S.A. 1991. Anatomy of a histogram. Technical Report CMU-CS-91–203, Carnegie Mellon University, Pittsburgh, PA.
Novak, C.L. and Shafer, S.A. 1992. Anatomy of a color histogram. In Proceedings of CVPR, Champaign, Il, pp. 599–605.
Ohlander, R., Price, K., and Reddy, D.R. 1978. Picture segmentation using a recursive region splitting method. Computer Graphics and Image Processing, 8:313–333.
1953. The Color Science. Optical Society of America. Thomas Y. Crowell Co.: New York, NY.
Oren, M.O. and Nayar, S.K. 1993. Generalization of the lambertian model. In Proceedings of the DARPA Image Understanding Workshop, Washington, DC, pp. 1037–1048.
Park, J.S. and Tou, J.T. 1990. Highlight separation and surface orientations for 3-d specular objects. In Proc. of IEEE Int. Conf. on Pattern Recog., Atlantic City, NJ, pp. 331–335.
Shafer, S.A. 1985. Using color to separate reflection components. COLOR Research and Application, 10:210–218.
Shafer, S.A., Klinker, G.J., and Kanade, T. 1990. A physical approach to color image understanding. Intern. Journal of Computer Vision, 4.
Tagare, H.D. and deFigueiredo, R.J. 1990. Simultaneous estimation of reflectance map and surface normal using photometric stereo. In Proc. of IEEE Int. Conf. on Computer Vision.
Tagare, H.D. and deFigueiredo, R.J. 1991. Photometric stereo for diffuse non-lambertian surface. IEEE Trans. PAMI, 13.
Tominaga, S. and Wandell, B. 1989. Standard surface-reflectance model and illuminant estimation. Journal of the Optical Society of America, 6.
Tominaga, S. and Wandell, B. 1990. Component estimation of surface spectral reflectance. Journal of the Optical Society of America, 7.
Torrance, K.E. and Sparrow, E.M. 1967. Theory for off-specular relfection from roughened surfaces. Journal of the Optical Society of America, 57:1105–1114.
Wandell, B.A. 1987. The synthesis and analysis of color images. IEEE Trans. on PAMI, 9:2–13.
Wolff, L.B. 1989. Using polarization to separate reflection components. In Proc. of IEEE Conference on Computer Vision and Pattern Recognition, San Diago, CA, pp. 363–369.
Wolff, L.B. 1991. Polarization Methods in Computer Vision. Ph.D. thesis, Department of Computer Science, Columbia University.
Wolff, L.B. 1993. Diffuse and specular reflection from dielectric surfaces. In Proceedings of the DARPA Image Understanding Workshop, Washington, DC, pp. 1025–1030.
Wyszecki, G. and Stiles, W.S. 1967. Color Science. John Wiley and Sons: New York, NY.
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Bajcsy, R., Lee, S.W. & Leonardis, A. Detection of diffuse and specular interface reflections and inter-reflections by color image segmentation. Int J Comput Vision 17, 241–272 (1996). https://doi.org/10.1007/BF00128233
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DOI: https://doi.org/10.1007/BF00128233