Illumination chromaticity estimation based on dichromatic reflection model and imperfect segmentation

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Abstract

The illumination chromaticity estimation based on the dichromatic reflection model has not been made practicable, since the method needs image segmentation beforehand. However, its two-dimensional model is sufficiently robust, when it is combined with the least square method. The proposed algorithm executes the color space division instead of the segmentation. The original image is divided into small color regions, each of which corresponds to one of color sub-spaces. Though this division is imperfect image segmentation, the illumination chromaticity estimation based on the chromaticity distribution in the color regions is possible. Experimental result shows that this method is also applicable to images of apparently matt surfaces. © 2009 Springer Berlin Heidelberg.

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APA

Tajima, J. (2009). Illumination chromaticity estimation based on dichromatic reflection model and imperfect segmentation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5646 LNCS, pp. 51–61). https://doi.org/10.1007/978-3-642-03265-3_6

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