基于小波包分析的催化剂表面图象识别  

IMAGE RECOGNITION OF CATALYST SURFACES BASED ON WAVELET PACKET ANALYSIS

作　　者：王积分[1] 阎炜[1] 段世铎[2] 冯霞[2] 

机构地区：[1]天津大学计算机科学与工程系 [2]天津大学化学系

出　　处：《机器人》1997年第1期22-27,共6页Robot

基　　金：国家自然科学基金

摘　　要：二维图象可以通过小波分解来进行信号的多分辨率分析．本文讨论了小波包分析技术及其在催化剂表面ＳＥＭ图象识别上的应用．从小波包中抽取的能量和纹理熵特征，在催化剂的分类与识别研究中，充分描述了表面图象在多标度空间上的信息分布．实验结果表明，小波包分解树是一种很好的模式特征描述。Two-dimensional images may be analyzed at mutliple resolution with the wavelet decomposition. This paper discusses the wavelet packet analysis and its applications to catalyst surface SEM image recognition. In the study on classification and recognition of catalyst surfaces, features were computed for each wavelet packet and they fully describe the information distribution of surface images at multiple scales space. Experiment results show that the wavelet packet tree is a good description about pattern features, and provides a new approach to image texture classification.

关 键 词：小波包分析 多分辨率分析 纹理识别 催化剂表面 

分 类 号：O643.36[理学—物理化学] TN911.1[理学—化学]