A Comprehensive Approach for Texture Classification

摘要：

Classification of textures based on wavelet pattern analysis is one of the most effective methods in texture classification. However using all frequency sub-bands in decomposition for classification may increase time complexity of classification algorithms. To reduce the time complexity, sub-bands with high energy and entropy are selected for classification. Fractal dimension can be used to select such significant sub-bands for decomposition at each level. Further statistical features of these significant sub-bands are given to modified K-NN classifier for classification. This paper describes texture classification using sub-bands of wavelets based on fractal dimensions and their results are compared with the results of texture classification using conventional features and also with different classifiers. Success rate is very high and time complexity is also reduced to the order of O(n).

关键词： Haar wavelet fractal dimension box counting Euclidean classifier K-NN classifier

作者: P.Ammi Reddy P.S.R.Chandra Murthy Dr.E.Sreenivasa Reddy

作者单位: Research Scholar,JNTU Kakinada,Kakinada, A.P., India Research Scholar, JNTU Kakinada,Kakinada, A.P., India Department of CSE Vasireddy Venkatadri Institute of Technology, Guntur, A.P., India

会议类型: 国际会议

会议名称: 2010 3rd IEEE International Conference on Computer Science and Information Technology(第三届IEEE计算机科学与信息技术国际会议 ICCSIT 2010)

会议地点: 成都

会议语种:英文

页码: 5-8

在线出版日期: 2010-07-07（万方平台首次上网日期，不代表论文的发表时间）