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color-receipe.pptx

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PRESETATION BY: TEJAS KAVITAKE DANIEL AKU YIRANG INTRODUCTION Color recipe prediction is a practical application of soft computing.  Color recipe prediction introduces “Neurofuzzy methodology” and “Computational intelligence”  It combines 3 principles of soft computing components: (i) Fuzzy systems (ii) Neural networks (iii) Genetic algorithms  i/p & o/p relation in color recipe prediction 16 inputs 10 outputs Target color Color recipe prediction system Surface spectral reflectance
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  PRESETATION BY: TEJAS KAVITAKE DANIEL AKU YIRAN  INTRODUCTION  Color recipe prediction is a practical application of soft computing.  Color recipe prediction introduces “ Neuro- fuzzy methodology” and “Computational intelligence”    It combines 3 principles of soft computing components: (i) Fuzzy systems (ii) Neural networks (iii) Genetic algorithms  i/p & o/p relation in color recipe prediction Target color 16 inputs Surface spectral reflectance White Black Green 1 Red 1 Green 2 Violet Red 2 Yellow 1 Yellow 2 Blue 10 outputs Color recipe prediction system  Main concerns in color recipe prediction  It is difficult to predict precise colorant concentrations{ we need to specify levels such as 0.01%}.  It is necessary to specify use of limited number of colorants and we need to avoid the use of complementary colorants.  The magnitude of mean-squared error of colorant vectors may not correspond exactly to that of color differences.  It is important to consider human visual sensitivity to color difference, which may be costly.  Some different combinations of colorant may have the same perceptual attributes of color as seen by humans.

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Jul 23, 2017
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