基于局部特征融合的人脸识别

提出了基于局部特征融合的人脸识别算法.首先把人脸图像分割为多个子图像,利用传统主成分分析的方法,对不同位置的子图像集分别建立不同的子空间并且抽取相应的局部特征.针对各局部特征,分别求出待识别图像对训练样本的隶属度.最后,基于模糊综合的原理对各局部特征进行数据融合,给出最终识别结果.实验结果表明,该算法能很好地融合人脸的局部信息,有效提高识别率.

Face Recognition Based on Local Feature Fusion

A face recognition method based on the fuzzy information fusion of the local features is proposed.Each original image is divided into many sub-images and all training sub-images from the same position construct a new training subset.The traditional PCA(principal component analysis) operates directly on a set of new training subsets respectively and a set of projection sub-spaces can be obtained.The local sub-feature of an unknown face can be extracted by projecting each sub-image onto the corresponding sub-space.According to these local sub-features,the membership grades of the test sub-images to the training sub-images can be determined.The identity of an unknown face image is determined by the fuzzy fusion which aggregates the local sub-features. The experiments on two standard face databases show the effectiveness of the proposed method.