基于离散余弦变换的人脸识别

Hongtao Yin, Jiaqing Qiao, Fu Ping
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引用次数: 7

摘要

人脸识别一直是人们关注的热点问题,现有的算法主要针对如何提高人脸识别的准确率,以及减少特征向量维数的使用。提出了一种基于离散余弦变换和svm特征分类的人脸识别方法。人脸识别中对DCT系数作为特征向量的有效选择问题。在SVM的训练过程中,将训练样本分为两部分,一部分使用训练样本的测试结果进行特征选择,并使用得到的准确率作为特征选择标准,本文提出的算法在ORL人脸图像标准库上进行了验证实验,取得了良好的效果,证明了其有效性和可靠性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Face Recognition with Discrete Cosine Transform
Face recognition has been a hot issue of concern to people, existing algorithms mainly for how to improve face recognition accuracy, and reduce the use of the feature vector dimension. A face recognition method based on the discrete cosine transform and SVM-based feature classification is presented. Face Recognition on the DCT coefficients as feature vectors in the problem of effective choice. In the training process of SVM, the training sample is divided into two parts, one part of the training samples using the test results of feature selection, and use the resulting accuracy rate as the feature selection criteria, the proposed algorithm on ORL face image standard library of verified experiments, and achieved good results prove the effective and reliable.
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