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2016 | OriginalPaper | Chapter

8. The Color Characteristic Model Based on Optimized BP Neural Network

Authors : Hongtao Miao, Lizheng Zhang

Published in: Advanced Graphic Communications, Packaging Technology and Materials

Publisher: Springer Singapore

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Abstract

Due to BP neural network’s own limitations, it requires a large number of samples for complex prediction, and its generalization ability is weak. This paper puts forward an optimized BP neural network algorithm. The methods focus on data normalization in order to improve maximum speed limit, the inertia constant, and fitness function to eventually optimize BP neural network weight value and threshold value to reduce its distribution range before using BP neural network for color prediction. Reducing the possibility of BP neural network prediction model getting into local optimization has good nonlinear fitting capability and higher prediction accuracy of color space conversion. If using in the ICC profile, it will ensure the accuracy of the color conversion.

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previous chapter The Experimental Research of Color Measurements with Spectrophotometer
next chapter The Model of Flexographic Spot-Color Matching Based on the Improved Kubelka–Munk Theory
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Metadata
Title
The Color Characteristic Model Based on Optimized BP Neural Network
Authors
Hongtao Miao
Lizheng Zhang
Copyright Year
2016
Publisher
Springer Singapore
Book
Advanced Graphic Communications, Packaging Technology and Materials

Print ISBN: 978-981-10-0070-6

Electronic ISBN: 978-981-10-0072-0

Copyright Year: 2016

DOI
https://doi.org/10.1007/978-981-10-0072-0_8