摘要
人脸自动识别是计算机模式识别领域的一个活跃课题,有着十分广泛的应用前景.文中提出了基于BP神经网络的人脸识别方法,讨论了人脸图像矢量的特征压缩问题、网络隐含层神经元数选取问题、网络输入矢量的标准化处理问题以及网络连接权值的初值选取问题.对由18人、每人12幅图像组成的人脸图像数据库做识别实验。
The automatic recognition of human faces is an active subject in the area of computer pattern recognition, which has a wide range of potential applications. A face recognition method is put forward based on the BP neural network. Also discussed are the problem of feature compression of a face image vector, the problem of determining the number of hidden layer's neural nodes, the problem of normalization of the input vector, and the problem of initialization of connection weights. Experiments have been conducted for a human face image database of 18 persons with 12 images per person. The recognition results show that compared with the 1 NN classifier, the neural network classifier designed can decrease the error rate efficiently.
出处
《计算机研究与发展》
EI
CSCD
北大核心
1999年第3期274-277,共4页
Journal of Computer Research and Development
基金
国家自然科学基金
关键词
神经网络
模式识别
人脸识别
图像识别
图像处理
neural network, feature compression, pattern recognition, face recognition