摘要
为了获取特种材料表面特有的激光散斑特征,建立了一套实验室内模拟远场测量系统。利用锁相放大器进行弱信号探测。采用小波分析的方法对数据进行了预处理,采用神经网络算法对实验数据进行了自动分类识别。实验结果表明,特种材料表面激光散斑的空间强度分布可以作为识别特种材料的依据之一,并为特种材料的识别提供了一种新的有效途径。
In order to acquire the special character of laser speckle reflected by special material surface, a measurement system simulating far-field is established in the laboratory. First,lock-in amplifier （LIA） is used for the detection of weak signal. Then,wavelet analysis is adopted for the data pretreatment, and neural-network is employed for automatic classification. Experiment result shows that the distribution of the laser speckle intensity in the space can be a kind of basis for special material, and it provides a new effective method for the recognition of special material.
出处
《红外与激光工程》
EI
CSCD
北大核心
2007年第2期186-188,232,共4页
Infrared and Laser Engineering
基金
国防重点实验室基金资助项目(00JS66.5.2QT0701)
关键词
激光散斑
小波分析
神经网络
特征提取与识别
Laser speckle
Wavelet analysis
Neural network
Feature extraction and recognition
