Title :
Reflectance-based classification of color edges
Author_Institution :
Informatics Inst., Fac. of Sci., Amsterdam, Netherlands
Abstract :
We aim at using color information to classify the physical nature of edges in video. To achieve physics-based edge classification, we first propose a novel approach to color edge detection by automatic noise-adaptive thresholding derived from sensor noise analysis. Then, we present a taxonomy on color edge types. As a result, a parameter-free edge classifier is obtained by labeling color transitions into one of the following types: (1) shadow-geometry, (2) highlight edges, (3) material edges. The proposed method is empirically verified on images showing complex real world scenes.
Keywords :
computer vision; edge detection; image classification; image colour analysis; image denoising; lighting; reflectivity; automatic noise-adaptive thresholding; color edge detection; color edges; color information; color transitions; edge highlighting; illuminant color; material edges; parameter-free edge classifier; real world scenes; reflectance-based image classification; sensor noise analysis; shadow geometry; taxonomy; video edges; Colored noise; Image edge detection; Image segmentation; Labeling; Layout; Lighting; Reflection; Reflectivity; Taxonomy; Video sequences;
Conference_Titel :
Computer Vision, 2003. Proceedings. Ninth IEEE International Conference on
Conference_Location :
Nice, France
Print_ISBN :
0-7695-1950-4
DOI :
10.1109/ICCV.2003.1238438