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Research on Color Space Conversion Model from CMYK to CIE-LAB Based on GRNN

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10749)

Abstract

In order to reproduce color information accurately in cross media transmission, a color space conversion model from CMYK color space to CIE-LAB based on generalized regression neural network (GRNN) was proposed. According to the structure and mathematical model of GRNN neural network, the CMYK-LAB color space conversion model was established. By training sample and comparing the mean square error of the sample data, the distribution coefficients were determined, and CMYK- LAB color space conversion model based on GRNN was eventually obtained and the accuracy was tested. According to these data, sample data and test data was determined. The results showed that color space conversion from CMYK to CIE-LAB on GRNN had faster conversion speed and accuracy compared with the color space conversion method based on BP neural network, the demand on printing industry can be met.

Keywords

Color space conversion Generalized regression neural network CMYK CIE-LAB BP neural network 

Notes

Acknowledgments

This work is supported by the Natural Science Fund for Colleges and Universities of Anhui Province (No. KJ2017ZD32) and the Innovation Fund for graduate students of Huaibei Normal University.

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.College of Computer Science and TechnologyHuaibei Normal UniversityAnhuiChina

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