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Face Recognition by Regularized-LDA Using PRM

机译:使用PRM的正则化LDA进行人脸识别

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摘要

Face recognition has received an increased attention from several years in the field of image analysis, pattern recognition, and computer vision. In this paper we propose a method to the problem of face recognition. The proposed method consists of two stages. In the first stage regularized linear discriminant analysis is used to extract the most significant and discriminant features and then in the second stage, these features are used by probabilistic reasoning model for classification of unknown face images. Here two databases, the ORL database and the UMIST database are used for experiments and to show the performance of the proposed method.
机译:在图像分析,模式识别和计算机视觉领域,人脸识别受到了越来越多的关注。在本文中,我们提出了一种解决人脸识别问题的方法。所提出的方法包括两个阶段。在第一阶段,使用正则化线性判别分析来提取最重要和最明显的特征,然后在第二阶段,概率推理模型将这些特征用于未知人脸图像的分类。这里,ORL数据库和UMIST数据库这两个数据库用于实验并显示了所提出方法的性能。

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