Neural network face recognition using statistical feature extraction

S. El-Khamy, O. Abdel-Alim, M. Saii
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引用次数: 14

Abstract

Recognition method of human face using statistical analysis feature extraction and a neural network algorithm is proposed. In the preprocessing step we detect the edges of the face image by using the Sobel algorithm. Then we propose a new method to transform the two-dimension black and white image to a one-dimension vector. Finally, based on the statistical analysis, we extract seven features. In the recognition step we use the fast backpropagation (FBP) algorithm. Computer simulation results with 100 test images of 10 persons (the images of each person in a various pauses, facial expression, and facial details) show that the proposed method yields a high recognition rate.
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基于统计特征提取的神经网络人脸识别
提出了一种基于统计分析、特征提取和神经网络的人脸识别方法。在预处理步骤中,我们使用Sobel算法检测人脸图像的边缘。然后提出了一种将二维黑白图像变换为一维矢量的新方法。最后,在统计分析的基础上,提取出7个特征。在识别步骤中,我们使用快速反向传播(FBP)算法。计算机仿真结果表明,该方法具有较高的识别率,其中包括10个人的100张测试图像(每个人在各种停顿、面部表情和面部细节中的图像)。
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