Research of Hi-Fi Color Separation Model Based on Cellular RBF Neural Network

SUN Xiao-peng, KONG Ling-jun, LIU Zhen

Packaging Engineering ›› 2013 ›› Issue (1) : 110-114.

Packaging Engineering ›› 2013 ›› Issue (1) : 110-114.

Research of Hi-Fi Color Separation Model Based on Cellular RBF Neural Network

  • SUN Xiao-peng1, LIU Zhen1, KONG Ling-jun2
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Abstract

Color separation models for seven-color printing system were established using cellular RBF neural network. Firstly, according to color space partition theory, the color space of the printing system was divided into 6 partitions by 7 primary colors. Dot areas, which were sampled from L of CIE L*a*b* with equal space, were then selected as training samples of RBF neural network model in each partition. Each partition was subdivided into several cells and the color separation algorithm based on RBF neural network model for each cell was established. Any target color would be separated into the CMYKRGB dot areas according to the color separation models of the numbered cell which were determined by the cell search algorithm proposed. The experiment result showed that the color separation algorithm can achieve high accuracy of color separation for seven-color print production.

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SUN Xiao-peng, KONG Ling-jun, LIU Zhen. Research of Hi-Fi Color Separation Model Based on Cellular RBF Neural Network[J]. Packaging Engineering. 2013(1): 110-114

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