Texture Recognition and Segmentation via Sparse Representation

摘要：

In this paper, a new algorithm for texture recognition and segmentation via sparse representation is presented. Firstly, we cast the texture recognition problem as one of classifying among multiple linear regression models, and solve the problem from a new perspective, sparse representation. This new theory decomposes the signal as a linear combination of the overcomplete dictionary by/,-minimization. Afterwards, as some texture class has been recognized, we are able to use the texture images structure feature, consistency, to segment all the parts of the texture image belonging to this class. Experiments are implemented on several synthetic texture images from publicly available database which demonstrates the effectiveness of our method.

关键词： Texture Recognition Image Segmentation Sparse Representation Compressed Sensing Irminimization.

作者: Fengxia Liu Zhongfu Ye Xue Wang Jisheng Dai

作者单位: Department of Electronic Engineering and Information Science University of Science and Technology of College of Electronic and Information Engineering Jiangsu University Zhenjiang, 212013, P. R. China

会议类型: 国际会议

会议名称: 2011 International Conference on Information and Industrial Electronics(2011年信息与工业电子国际会议 ICIIE 2011)

会议地点: 成都

会议语种:英文

页码: 409-413

在线出版日期: 2011-01-14（万方平台首次上网日期，不代表论文的发表时间）