Classifying color transitions into shadow-geometry, illumination, highlight or material edges

We aim at using color information to classify the physical nature of a color edge: that is whether the transition is due to shadows, abrupt surface orientation changes, illumination, highlights or material changes. To achieve a physics-based edge classification, we propose a taxonomy of color invariant edges. The taxonomy is based upon the sensitivity of the various color edges with respect to different imaging dependencies i.e. shadows, object shape, shading (i.e. illumination intensity changes), highlights and material characteristics. From this taxonomy, the edge classifier is derived labeling color transitions into the following types: (1) shadow, geometry or shading edges, (2) highlight edges, (3) material edges. Experiments conducted with the edge classification technique on color and hyperspectral images show that the proposed method successfully discriminates the different edge types.

[1]  Theo Gevers,et al.  Detection and Classification of Hyper-Spectral Edges , 1999, BMVC.

[2]  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.

[3]  Silvano Di Zenzo,et al.  A note on the gradient of a multi-image , 1986, Comput. Vis. Graph. Image Process..

[4]  Arnold W. M. Smeulders,et al.  Color-based object recognition , 1997, Pattern Recognit..

[5]  Guillermo Sapiro,et al.  Anisotropic diffusion of color images , 1996, Electronic Imaging.

[6]  Glenn Healey,et al.  Segmenting images using normalized color , 1992, IEEE Trans. Syst. Man Cybern..