摘要
根据NMI特征和Jan Flusser提出的仿射不变矩各自的特点和适用条件,提出了一种组合不变矩。利用组合不变矩提取图像的不变特征向量,并结合Fisher线性判别准则,实现了对空中目标的Fisher线性判别器(FLDA)的分类识别。同时,考虑到识别的快速性方面,对FLDA进行了改进,提出了主分量分析(PCA)与FLDA相结合的识别算法。仿真实验结果表明,该方法具有较高的识别精度和速度。
A new combined invariant moment was presented according to the characteristics of NMT＇s feature and affine invariant moment proposed by Jan Flusser with their application conditions. The feature vector of the aerial target was extracted by using combined invariant moments. With the help of Fisher linear discriminant rule, the aerial target classification was implemented successfully based on Fisher Linear Discriminant Analysis （FLDA）. At the same time, considering the speediness requirement of recognition, the FLDA was improved, which combined Principal Components Analysis （PCA） with FLDA. The experimental comparisons showed that the proposed method achieves good classification precision and speed.
出处
《电光与控制》
北大核心
2009年第7期21-24,44,F0003,共6页
Electronics Optics & Control
基金
火力控制技术国防科技重点实验室资助(05C52007)
关键词
图像识别
目标识别
仿射不变矩
组合不变矩
Fisher线性判别器
主分量分析
image recognition
target recognition
affine invariant moment
combined invariant moment
Fisher linear discriminant analysis
principal component analysis
