Unsupervised Texture Segmentation Based on Redundant Wavelet Transform

摘要：

The algorithm of Redundant Wavelet Transform (RWT) and laws texture measurement is proposed and applied to image segmentation. Based on the characteristics of the indentation images, this article uses texture features to extract the indentation silhouette from the point view of texture segmentation. We adopt Redundant Wavelet Transform and laws texture measurement algorithm to describe the texture characteristics of the indentation image, forming a n-dimensional feature vector, introducing texture features smoothing algorithm based on quadrant to smooth the features. Finally we combine with the improved k-means clustering algorithm to get texture segmentation result. The experiment demonstrates that in the material Vickers hardness image segmentation the proposed algorithm was significantly effective and robust.

关键词： RWT laws texture measurement improved k-means clustering algorithm Texture segmentation

作者: Guitang Wang Wenjuan Liu Ruihuang Wang Xiaowu Huang Feng Wang

作者单位: School of Information Engineering,Guangdong University of Technology Guangzhou, P.R.China School of Information Engineering,Guangdong University of Technology Guangzhou, P. R. China School of Information Engineering, Guangdong University of Technology Guangzhou, P. R. China

会议类型: 国际会议

会议名称: 2010 Third International Symposium on Intelligent Ubiquitous and Education(2010年第三届智能普适计算与教育国际研讨会 IUCE 2010)

会议地点: 北京

会议语种:英文

页码: 227-230

在线出版日期: 2010-09-18（万方平台首次上网日期，不代表论文的发表时间）