Halftone spectral prediction model based on fuzzy local information C-means clustering algorithm

被引：0

作者：

Xu, Junfei ^{[1
]}

Zhou, Xiaofan ^{[1
]}

Shi, Yong ^{[1
]}

机构：

[1] Jiangsu Provincial Key Laboratory of Pulp and Paper Science and Technology,, Nanjing Forestry University,, Nanjing,, 210037, Jiangsu

来源：

Guangxue Xuebao/Acta Optica Sinica | 2015年 / 35卷 / 09期

关键词：

Color optics; Core-fringe model; Fuzzy local information C-means clustering algorithm; Lambert-Beer law; Spectral reflectivity prediction;

D O I：

10.3788/AOS201535.0933001

中图分类号：

学科分类号：

摘要：

A spectral prediction model is proposed and applied to halftone print on paper substrate. The single dot of halftone print consists of several regions: core area of the dot has uniform thickness and the same thickness of ink-layer as that of the solid print. The edge regions have fuzzy thickness distribution function, and the thickness of ink-layer is thinner than that of the solid print. The single dots of halftone print are clustered based on the density of pixel by the fuzzy local information C-means clustering algorithm, the well-bedded halftone dots can be achieved by the algorithm, and the fractional surface coverage of each cluster region can be calculated. A new algorithm model for halftone spectral prediction is established, and the spectral reflectivity predicted by the algorithm is well consisted with that measured through the halftone presswork proof, demonstrating that the prediction accuracy of the model is higher. ï¿½, 2015, Chinese Optical Society. All right reserved.

引用

页数：8