Paper
19 January 2009 Application of categorical colors to area segmentation for road image
T. Ashiguchi, T. Yaguchi, K. Kijima, S. Ishida, Y. Nakanishi, K. Shoji, M. Ayama
Author Affiliations +
Proceedings Volume 7241, Color Imaging XIV: Displaying, Processing, Hardcopy, and Applications; 72410K (2009) https://doi.org/10.1117/12.805769
Event: IS&T/SPIE Electronic Imaging, 2009, San Jose, California, United States
Abstract
Humans can put different colors together and categorize them as "red", "yellow", or "orange" etc. This is called categorical color perception. We applied this property of human color vision to area segmentation for road images in order to compensate color tone change of road images depending on light condition on a road. Basic map of categorical colors is constructed in the L*a*b* space based on the color naming experiment. Area segmentation was done by assigning one of the 14 categorical colors to each pixel. Results were successful, even without any noise reduction technique, A shifted database of categorical colors for images with orangish tone is also prepared by trial and error. Pseudo-color-constancy is successfully obtained for the images of orangish tones using the shifted database. To deal with the lightness change depending on the change of sunlight along the time of day, an appropriate value was added to the lightness of each pixel of the original image. Satisfiable area segmentation was obtained in this case, too. This method indicates the possibility of implementation of color constancy property for color image processing of road scene.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
T. Ashiguchi, T. Yaguchi, K. Kijima, S. Ishida, Y. Nakanishi, K. Shoji, and M. Ayama "Application of categorical colors to area segmentation for road image", Proc. SPIE 7241, Color Imaging XIV: Displaying, Processing, Hardcopy, and Applications, 72410K (19 January 2009); https://doi.org/10.1117/12.805769
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Cited by 3 scholarly publications.
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KEYWORDS
Image segmentation

Roads

Databases

Color vision

Color image processing

Image processing

Light sources and illumination

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