Feature extraction using dual-tree complex wavelet transform and gray level co-occurrence matrix
Feature extraction using dual-tree complex wavelet transform and gray level co-occurrence matrix
复制标题
使用双树复小波变换和灰度共生矩阵进行特征提取
DOI：
10.1016/j.neucom.2016.02.061
复制
发表时间：
2016-07-12
期刊：
影响因子：
6
通讯作者：
Yang, Guowei
中科院分区：
文献类型：
--
作者：
Yang, Peng;Yang, Guowei
提出了一种新的纹理特征提取方法。该方法首先对原始图像进行双树复小波变换，得到6个方向的子图像。然后计算各子图像的灰度共生矩阵，并利用相应的统计值构造最终的特征向量。实验结果表明，该方法具有较好的鲁棒性，与传统方法相比，能够获得更高的纹理分类准确率。(C)2016爱思唯尔B.V.保留所有权利。
This paper introduces a new feature extraction method for texture classification application. In the proposed method, dual-tree complex wavelet transform is first performed on the original image to obtain sub-images at six directions. After that gray level co-occurrence matrix of each sub-image is calculated and the corresponding statistical values are used to construct the final feature vector. The experimental results demonstrate that our proposed method has the property of robustness, and can achieve higher texture classification accuracy rate than the conventional methods. (C) 2016 Elsevier B.V. All rights reserved.