【摘要】 提出了基于BP神经网络的主分量人脸识别算法。该算法首先用小波变换对人脸图像进行小波分解,形成低频小波子图,然后用主分量分析法构造特征脸子空间,将人脸图像在特征空间的投影作为BP神经网络的输入,由BP神经网络和后验概率转换器构成人脸识别器。针对ORL人脸库的实验结果表明该方法具有较高的识别率。更多还原

【Abstract】 BP neural network combined with principal component analysis is applied to human face recognition.After extracting low frequency sub-band of face image in wavelet transform,the eigenface space is constructed by PCA.Then all samples are projected into the subspace,the coefficient of every sample is inputted to BP neural network,and the face recognizer consists of BP neural network and post-probability converter.The experiments on ORL face database indicate the recognition ratio is greatly improved.更多还原