基于小波变换与小域特征模糊融合的人脸识别

小波变换是一种很好的图像压缩方法,利用小波变换对人脸图像进行三次小波分解,并将低频分量分割成为7个子图像。鉴于人脸上的各小域子图像信息的相互独立性。先利用小域子图像实现软分类,然后使用传统奇异值分解(SVD)法提取出各小域子图像的奇异值(SV),构造出小域奇异值特征向量,给出待识别图像对训练样本图像的隶属度,并采用模糊融合的方法对小域特征进行数据融合,获得识别结果。实验结果表明,该方法实现起来简单、识别速度快,具有很高的识别率。

Face recognition based on wavelet transform and small-area feature fuzzy fusion

Wavelet transform is a very good method about image compression.Human face images are decomposed using wavelet transform,and parts of low frequency are divided into seven sub-images.Owing to information independence of facial small-area sub-images,soft recognition based on small-area sub-images can be implemented firstly.The traditional SVD (singu- lar value decomposition) operates directly on a set of new training sub-images respectively.A set of small-area SV can be ex- tracted and then a set of small-area SV eigenvector can be obtained.According to these small-area 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 small-area sub-features.The experiments show that the proposed method has the char- acteristics of simple realization,rapid recognition speed and high recognition rate.