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http://dx.doi.org/10.3745/KIPSTB.2011.18B.2.051

Acquisition of Intrinsic Image by Omnidirectional Projection of ROI and Translation of White Patch on the X-chromaticity Space  

Kim, Dal-Hyoun (충북대학교 컴퓨터공학과)
Hwang, Dong-Guk (충북대학교 컴퓨터공학과)
Lee, Woo-Ram (충북대학교 컴퓨터공학과)
Jun, Byoung-Min (충북대학교 전기전자컴퓨터공학부)
Publication Information
The KIPS Transactions:PartB / v.18B, no.2, 2011 , pp. 51-56 More about this Journal
Abstract
Algorithms for intrinsic images reduce color differences in RGB images caused by the temperature of black-body radiators. Based on the reference light and detecting single invariant direction, these algorithms are weak in real images which can have multiple invariant directions when the scene illuminant is a colored illuminant. To solve these problems, this paper proposes a method of acquiring an intrinsic image by omnidirectional projection of an ROI and a translation of white patch in the ${\chi}$-chromaticity space. Because it is not easy to analyze an image in the three-dimensional RGB space, the ${\chi}$-chromaticity is also employed without the brightness factor in this paper. After the effect of the colored illuminant is decreased by a translation of white patch, an invariant direction is detected by omnidirectional projection of an ROI in this chromaticity space. In case the RGB image has multiple invariant directions, only one ROI is selected with the bin, which has the highest frequency in 3D histogram. And then the two operations, projection and inverse transformation, make intrinsic image acquired. In the experiments, test images were four datasets presented by Ebner and evaluation methods was the follows: standard deviation of the invariant direction, the constancy measure, the color space measure and the color constancy measure. The experimental results showed that the proposed method had lower standard deviation than the entropy, that its performance was two times higher than the compared algorithm.
Keywords
Intrinsic Image; Color Constancy; Invariant Direction; Omnidirectional Projection; White Patch;
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  • Reference
1 G. D. Finlayson and M. S. Drew, "4-Sensor Camera Calibration for Image Representation Invariant to Shading, Shadows, Lighting, and Specularities," Proceedings of the Eighth IEEE Internatinal Conference on Computer Vision, Vol.2, pp.473-480, 2001.   DOI
2 K. Barnard, L. Martin, B. Funt and A. Coath, "A data set for color research," Color Research and Applications, Vol.27, No.3, pp.148-152, 2002.
3 M. Ebner, "Color Constancy Based on Local Space Average Color," Machine Vision and Applications, Vol.11, No.5, pp.283-301, July, 2009.
4 M. Ebner, "Evolving color constancy," Special Issue on Evolutionary Computer Vision and Image Understanding of Pattern Recognition Letters, Vol.27, No.11, pp.1220-1229, 2006.
5 H. Haken and H. C. Wolf, "Atom-und Quantenphysik: Einfv hrung in die Experimentellen und Theoretischen Grundlagen," vierte edn, Springer-Verlag, Berlin, Heidelberg, 1990.
6 B. Jahne, Digitale Bildverarbeitung, fifth edn, Springer-Verlag, Berlin, 2002.
7 M. F. Tappen, W. T. Freeman, and E. H. Adelson, "Recovering Intrinsic images from a single image," Technical Report AI Memo 2002-015, MIT, Artificial Intelligence Laboratory, 2002.
8 G. D. Finlayson and S. D. Hordley, "Color constancy at a pixel," Journal of the Optical Society of America, Vol.18, No.2, pp.253-264, 2001.   DOI   ScienceOn
9 G. D. Finlayson, M. S. Drew and C. Lu, "Intrinsic images by entropy minimization," Proceedings of the 8th European Conference on Computer Vision, Part III, Prague, pp.582-595, 2004.
10 M. S. Drew, G. D. Finalyson, and S. D. Hordley, "Recovery of chromaticity image free from shadows via illumination invariance," ICCV'03 Workshop on Color and Photometric Methods in Computer Vision, Nice, pp.32-39, 2003.
11 He Qiang and Henry Chu Chee-Hung, "Recovering Intrinsic images from Weighted Edge Maps," Second International Conference on Intelligent Information Hiding and Multimedia Signal Processing, pp.159-162, 2006.
12 J. P. Renno, D. Makris, T. Ellis, and G. A. Jones, "Application and Evaluation of Colour Constancy in Visual Surveillance," Proceedings of the 14th International Conference on Computer Communications and Networks, pp.301-308, 2005.   DOI
13 S. Zeki, 'A Vision of the Brain', Oxford, Blackwell Science, 1993.
14 M. Ebner, "A parallel algorithm for color constancy," Journal of Paralled and Distributed Computing, Vol.64, No.1, pp.79-88, 2004.   DOI   ScienceOn
15 M. Ebner, Color Constancy, WILEY, 2007.
16 S. D. Hordley, "Scene Illuminant Estimation: Past, Present, and Future," Color Research and Application, Vol.31, No.4, pp.303-314, August, 2006.   DOI   ScienceOn