Temporal-color space analysis of reflection

A method to analyze a sequence of color images is proposed. A series of images is examined in a four-dimensional space, which is called the temporal-color space, the axes of which are the three color axes (RGB) and one temporal axis. The significance of the temporal-color space lies in its ability to represent the change of image color with time. A conventional color space analysis yields the histogram of the colors in an image only at an instance of time. Conceptually, the two reflection components from the dichromatic reflection model, the specular reflection component and the body reflection component, form two subspaces in the temporal-color space. These two components can be extracted by principal component analysis. Using this fact, real color images are analyzed, and the two reflection components are separated successfully.<<ETX>>

[1]  Mark S. Drew,et al.  Separating a Color Signal into Illumination and Surface Reflectance Components: Theory and Applications , 1990, IEEE Trans. Pattern Anal. Mach. Intell..

[2]  Katsushi Ikeuchi,et al.  Implementation and Evaluation of a Three-Dimensional Photometric Sampler , 1992 .

[3]  K. Torrance,et al.  Theory for off-specular reflection from roughened surfaces , 1967 .

[4]  Katsushi Ikeuchi,et al.  Determining Surface Orientations of Specular Surfaces by Using the Photometric Stereo Method , 1981, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[5]  Lawrence B. Wolff,et al.  Using polarization to separate reflection components , 1989, Proceedings CVPR '89: IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[6]  Steven A. Shafer,et al.  Using color to separate reflection components , 1985 .

[7]  Steven A. Shafer,et al.  Anatomy of a color histogram , 1992, Proceedings 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[8]  Takeo Kanade,et al.  Determining shape and reflectance of hybrid surfaces by photometric sampling , 1989, IEEE Trans. Robotics Autom..

[9]  Hsien-Che Lee,et al.  Modeling Light Reflection for Computer Color Vision , 1990, IEEE Trans. Pattern Anal. Mach. Intell..

[10]  F. E. Nicodemus,et al.  Geometrical considerations and nomenclature for reflectance , 1977 .

[11]  P. Beckmann,et al.  The scattering of electromagnetic waves from rough surfaces , 1963 .

[12]  Shree K. Nayar,et al.  Removal of specularities using color and polarization , 1993, Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.

[13]  R. Bajcsy,et al.  Color image segmentation with detection of highlights and local illumination induced by inter-reflections , 1990, [1990] Proceedings. 10th International Conference on Pattern Recognition.

[14]  K Sasaki,et al.  Component analysis of spatial and spectral patterns in multispectral images. I. Basis. , 1987, Journal of the Optical Society of America. A, Optics and image science.

[15]  Steven A. Shafer.  Optical Phenomena in Computer Vision , 1984 .

[16]  Sang Wook Lee,et al.  Detection of specularity using colour and multiple views , 1992, Image Vis. Comput..

[17]  B. Wandell,et al.  Standard surface-reflectance model and illuminant estimation , 1989 .

[18]  B. Wandell,et al.  Component estimation of surface spectral reflectance , 1990 .

[19]  H C Lee,et al.  Method for computing the scene-illuminant chromaticity from specular highlights. , 1986, Journal of the Optical Society of America. A, Optics and image science.

[20]  Takeo Kanade,et al.  Surface Reflection: Physical and Geometrical Perspectives , 1989, IEEE Trans. Pattern Anal. Mach. Intell..

[21]  R. M. Haralick,et al.  Pattern recognition with measurement space and spatial clustering for multiple images , 1969 .

[22]  Berthold K. P. Horn.  SHAPE FROM SHADING: A METHOD FOR OBTAINING THE SHAPE OF A SMOOTH OPAQUE OBJECT FROM ONE VIEW , 1970 .

[23]  Katsushi Ikeuchi,et al.  Numerical Shape from Shading and Occluding Boundaries , 1981, Artif. Intell..

[24]  Robert J. Woodham,et al.  Photometric Stereo: A Reflectance Map Technique For Determining Surface Orientation From Image Intensity , 1979, Optics & Photonics.

[25]  Thomas O. Binford,et al.  Local shape from specularity , 1988, Comput. Vis. Graph. Image Process..

[26]  Steven A. Shafer,et al.  Obtaining accurate color images for machine-vision research , 1990, Electronic Imaging.

[27]  Mark S. Drew,et al.  Color Space Analysis of Mutual Illumination , 1992, IEEE Trans. Pattern Anal. Mach. Intell..

[28]  Glenn Healey,et al.  Using color for geometry-insensitive segmentation , 1989 .

[29]  Berthold K. P. Horn.  Obtaining shape from shading information , 1989 .

[30]  Katsushi Ikeuchi,et al.  Temporal-color space analysis of reflection , 1994 .