Face recognition using neural networks

N. Jamil, S. Lqbal, N. Iqbal
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引用次数: 171

Abstract

In this paper we depict an experiment to the face recognition problem by combining eigenfaces and neural network. Eigenfaces are applied to extract the relevant information in a face image, which are important for identification. Using this we can represent face pictures with several coefficients (about twenty) instead of having to use the whole picture. Neural networks are used to recognize the face through learning correct classification of the coefficients calculated by the eigenface algorithm. The network is first trained on the pictures from the face database, and then it is used to identify the face pictures given to it. Eight subjects (persons) were used in a database of 80 face images. A recognition accuracy of 95.6% was achieved with vertically oriented frontal views of a human face.
利用神经网络进行人脸识别
本文描述了一个结合特征脸和神经网络的人脸识别实验。特征脸用于提取人脸图像中的相关信息,这些信息对人脸识别至关重要。使用这种方法,我们可以用几个系数(大约20)来表示人脸图像,而不必使用整个图像。神经网络通过学习特征脸算法计算的系数的正确分类来识别人脸。该网络首先对人脸数据库中的图片进行训练,然后用于识别给定的人脸图片。8名受试者(人)被用于80张人脸图像的数据库中。在垂直方向的人脸正面视图下,识别准确率达到95.6%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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