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Accurate reflectance prediction in multi-angle measurement

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This study focuses on finding the best viewing angles so that accurate reflectance prediction could be achieved in multi-angle measurement of metallic and pearlescent samples. The root mean square error (RMSE) produced by the reconstruction from the first seven Principle component vectors (PCV), the cumulative contribution being 99.92 percent, were analyzed to find the best viewing angles 10°, 65°, 95°, 120°, 145°, 155° and 170° in clock wise direction from the surface for illumination angle of 45°. The error difference resulted by prediction using cubic interpolation and proposed Principle component analysis (PCA) based method were compared. The prediction by PCA based method outperforms the prediction by cubic interpolation. The method can be employed not only to metallic and pearlescent samples but to all non lambertian surfaces.
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Document Type: Research Article

Publication date: January 1, 2008

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  • Started in 2002 and merged with the Color and Imaging Conference (CIC) in 2014, CGIV covered a wide range of topics related to colour and visual information, including color science, computational color, color in computer graphics, color reproduction, volor vision/psychophysics, color image quality, color image processing, and multispectral color science. Drawing papers from researchers, scientists, and engineers worldwide, DGIV offered attendees a unique experience to share with colleagues in industry and academic, and on national and international standards committees. Held every year in Europe, DGIV papers were more academic in their focus and had high student participation rates.

    Please note: For purposes of its Digital Library content, IS&T defines Open Access as papers that will be downloadable in their entirety for free in perpetuity. Copyright restrictions on papers vary; see individual papers for details.

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