Performance analysis of face recognition algorithms

Fatih Ilkbahar, R. Kara
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引用次数: 4

Abstract

The usage areas of biometric systems are becoming widespread in today's technology. Face recognition systems among biometric systems; Ease of use, reliability, cost, etc., the preference between public institutions, commercial enterprises and researchers is increasing. In this study, it is suggested that students should use face recognition system instead of traditional methods of absenteeism in education and training institutions. It is very important that face recognition systems work quickly with matching people correctly. In this study, the training and recognition times of Eigenfaces, Fisherfaces and Local Binary Pattern algorithms used in face recognition systems are calculated by using Visual C ++ and Python programming languages using ORL dataset.
人脸识别算法的性能分析
在当今的技术中,生物识别系统的应用领域越来越广泛。生物识别系统中的人脸识别系统;易用性,可靠性,成本等,公共机构,商业企业和研究人员的偏好正在增加。在本研究中,建议在教育培训机构使用人脸识别系统代替传统的缺勤方法。人脸识别系统的快速工作和正确匹配是非常重要的。本研究以ORL数据集为基础,利用Visual c++和Python编程语言,计算了人脸识别系统中所使用的特征脸、渔民脸和局部二进制模式算法的训练和识别次数。
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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