基于Brushlet复特征的纹理分类

钟桦; 肖竹; 焦李成

doi:10.3724/SP.J.1146.2006.00356

基于Brushlet复特征的纹理分类

doi: 10.3724/SP.J.1146.2006.00356

基金项目:

国家自然科学基金(60505010, 60472084)和国家973重点基础研究发展规划项目基金(2001CB309403)资助课题

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出版历程
- 收稿日期: 2006-03-27
- 修回日期: 2006-09-04
- 刊出日期: 2007-10-19

Texture Classification Using Complex Feature of Brushlet

摘要

摘要: Brushlet是一种新的图像方向信息分析工具，其能量特征已被应用于纹理分割、分类以及去噪等领域。该文利用Brushlet变换为复函数这一特性，提取其能量及相位信息作为纹理分类特征。通过对Brodatz纹理图像库中均匀、非均匀以及全部图像进行分类实验，较之单一能量特征的分类方法，Brushlet复特征取得了更好的分类性能。
- Brushlet变换;方向性;纹理图像;相位特征
Abstract: Brushlet is a novel tool for image orientation analysis, whose energy feature is adopted in texture segmentation, image classification and denoising. In this paper, the property of Brushlet is used: the transform is a complex value function with a phase, the energy and phase information are adopted as a fused feature for texture classification. Experiments on homogeneous, inhomogeneous images and total Brodatz texture alblum prove that the complex feature of Brushlet outperforms the method based on single energy.

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参考文献(1)

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