A Study on Methods for Rotation Invariant Image Recognition Based on Texture Characteristic

摘要：

Three kinds of rotation invariant image classification recognition algorithms based on texture characteristic are proposed. All the methods proposed are based on rotation-to-shift. First, the texture image is transformed by log-polar transform or Radon transform to convert the rotation to shift, then filter the transformed image using dual-tree complex wavelet transform(DT-CWT) or discrete stationary wavelet transform(SWT) which is shift invariant to eliminate the shift.The rotation invariant feature vector is composed of the energies of the filter subbands and the SVM algorithm is used to classify at last. The paper experiments three feature extraction methods: log-polar transform combined DT-CWT, Radon transform combined DT-CWT and Radon transform combined SWT.Analyze the experiment results and compare the best one with other rotation invariant texture classification algorithm, the experiment results show that it can improve the classification rate effectively.

关键词： rotation invariant texture classification log-polar transform radon transform dual-tree complex wavelet transform discrete stationary wavelet transform

作者: Yan Shang Tao An Zhiyong Meng

作者单位: Hebei University of Science and Technology Hebust Shijiazhuang,China

会议类型: 国际会议

会议名称: The 2010 International Conference on Computer Application and System Modeling(2010计算机应用与系统建模国际会议 ICCASM 2010)

会议地点: 太原

会议语种:英文

页码: 568-571

在线出版日期: 2010-10-22（万方平台首次上网日期，不代表论文的发表时间）