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林业科学 ›› 2005, Vol. 41 ›› Issue (2): 100-105.doi: 10.11707/j.1001-7488.20050217

• 论文及研究报告 • 上一篇    下一篇

基于小波的木材纹理分频信息提取与分析

于海鹏 刘一星 孙建平   

  1. 东北林业大学生物质材料科学与技术教育部重点实验室,哈尔滨150040
  • 收稿日期:2004-06-22 修回日期:1900-01-01 出版日期:2005-03-25 发布日期:2005-03-25

Separated Frequency Features Extraction and Analysis of Wood Texture Based on Wavelet

Yu Haipeng,Liu Yixing,Sun Jianping   

  1. Key Laboratory of Bio-Based Material Science and Technology of Ministry of Education, Northeast Forestry University Harbin 150040
  • Received:2004-06-22 Revised:1900-01-01 Online:2005-03-25 Published:2005-03-25

摘要:

通过引入小波方法,对木材纹理进行了多尺度的频谱分解,并利用所得到的特征向量分析了水平、垂直和对角方向上的木材纹理频率分布特点,比较了针叶树材与阔叶树材、径向切面与弦向切面木材纹理的统计差异。并在试验基础上,提出了以小波分解子图像能量值的标准差进行木材纹理最佳分解尺度的筛选,探索出滤波长度取8、分解尺度取2对充分表现木材纹理特征最为适宜。同时还发现可将垂直中高频分量HL和低频分量LL的能量值作为木材纹理区别与归类的重要参数,将EHL/ELH值作为木材纹理的方向性量度

关键词: 木材, 纹理, 小波

Abstract:

Based on wavelet method, it realized multi_resolutional spectrum decomposition of wood surface texture, and analyzed frequency traits of wood texture at horizontal, vertical and angular directions by eigenvalues from decomposition subsections, furthermore it compared texture differences of softwood with those of hardwood, and radial section with tangential section. It proposed to use standard deviation of sub-image energies to select an optimal wavelet decomposition scale for wood texture, and found out a better selection of filter length at 8 and a best decomposition scale at 2 for wood. Also in this paper, it indicated that energies of subsection HL and LL can be used as key parameters for texture distinction and classification, and EHL/ELH can be used to declare texture direction of wood.

Key words: wood, texture, wavelet