人脸识别技术在商业和法律上有广泛的应用前景,在安全监控中也大有用武之地.其主要任务是利用已有的人脸图象库,识别静止的或视频图象中的一张或多张人脸.从抽取具有统计不相关的模式特征着手,通过基于小波变换的图象分解和KL变换等处理,避开人脸识别的小样本集的局限,并通过运用具有统计不相关性的最佳鉴别变换,来抽取人脸的有效鉴别特征.同时,利用多特征多分类器组合的方法对图象进行识别.该方法在ORL人脸图象库上进行实验,得到识别错误率为2%的实验结果,这是目前在此人脸图象数据库上所得到的最好的实验结果.

Face recognition technology (FRT) has numerous commercial and law enforcement applications, especially in video surveillance. The primary task at hand, given still or video images, requires the identification of one or more persons using a database of stored face images. Based on Fisher discriminant criterion, In order to extract features by using the uncorrelated discriminant transformation, we use orthogonal wavelet transformation and KL transformation to process the face images at first. According to peoples' recognition experience, we use multi-feature and multi-classifier combination to give out the classification results. Experiments on ORL database obtained an error rate of 2%, which is the best result on this database up to now. Experimental results also show that this method does not sensitive to the pose and expression of human faces.