文件名称:Subpattern-based_principal___component_analysis.zi
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子模式主成分分析首先对原始图像分块,然后对相同位置的子图像分别建立子图像集,在每一个子图像集内使用PCA方法提取特征,建立子空间。对待识别图像,经相同分块后,分别将子图像向对应的子空间投影,提取特征。最后根据最近邻原则进行分类。-Sub-mode principal component analysis first of the original image block, and then the same sub-image, respectively, the location of the establishment of sub-image set, in each sub-image set to use PCA to extract the features, the establishment of sub-space. Treatment to identify images, by the same block, the respective sub-image to the corresponding sub-space projection, feature extraction. Finally, according to the principle of nearest neighbor classification.
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extraction
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matlab
图像分块
最近邻
识别
projection
of
image
features
图像
识别
图像
相同
matlab
特征
分类
image
analysis
子图像
feature
extraction
in
matlab
extraction
of
an
image
matlab
图像分块
最近邻
识别
projection
of
image
features
图像
识别
图像
相同
matlab
特征
分类
image
analysis
子图像
feature
extraction
in
matlab
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Subpattern-based_principal___component_analysis.pdf