Paper Web Defection Segmentation Using Gauss-Markov Random Field Texture Features

摘要：

In order to segment paper web defections effectively, texture features, based on the Gauss-Markov random field model, were used in this paper. By introducing the characteristics of paper web texture features, the maximum difference of the local texture parameters w1, w2, w3 and w4 of the Gauss-Markov random field model was used as a judgment index for web defection segmentation. A dirty spot defection was segmented by this method and its result shows that the paper web defections can be effectively segmented by the judgment index. The max difference of the local texture parameters of the Gauss-Markov random field model can be used as the judgment index to segment the defections in the paper web, which has the characteristics of nature texture.

关键词： Gauss-Markov random field web defection textile features

作者: Xun Huang Jixian Dong Mengxiao Wang

作者单位: Department of Mechanic and Electronic Engineering Shaanxi University of Science and Technology, Xian Yang, 712081, China

会议类型: 国际会议

会议名称: 2011 International Conference on Image Analysis and Signal Processing(2011第三届图像分析与信号处理国际会议 IASP 2011)

会议地点: 武汉

会议语种:英文

页码: 167-170

在线出版日期: 2011-10-21（万方平台首次上网日期，不代表论文的发表时间）