Since illumination condition effects recognition ratio for human face greatly, while average gray value of every face image is different, we must standardize gray value of face images.
由于人脸识别率受照明条件的影响较大，而各个人脸图像的平均灰度值各不相同，所以必须对人脸图像进行灰度归一化。
Use the image illumination correction, reduce the dimension of face images and different lighting conditions, the use of human face images improved the BP neural network for recognition.
运用了图像进行光照校正，人脸图像进行降维及不同的光照条件下的人脸图像运用改进型的BP神经网络对进行识别。
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