A Review Paper on Facial Recognition Techniques in E-business

Tiyani Christopher Hlongwane, Topside E. Mathonsi, D. D. du Plessis, Tonderai Muchenje
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Abstract

Facial recognition is a biological biometric feature that allows a person to be identified from a digital image. The face is known as the most recognizable aspect of human anatomy and acts like a human being’s first distinguishing feature. There are different techniques that can be used for the classification of data, two widely used techniques for data classification and dimension reduction are Principle Components Analysis (PCA) and Linear Discriminant Analysis (LDA). Facial recognition techniques have been comprehensively studied and applied in e-business. To reduce the False Rejection Rate (FRR) and False Acceptance Rate (FAR) during the recognition process, this review looks at the methods and the parameters that affect the facial recognition. Furthermore, we outline the strengths and challenges of these techniques. This comprehensive study serves as a starting point and a guide for everyone interested in exploring facial recognition techniques research area. The paper presents the conclusion and future work.
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电子商务中的人脸识别技术综述
面部识别是一种生物特征,可以从数字图像中识别出一个人。脸被认为是人体解剖结构中最容易识别的部分,也是人类的第一个特征。有不同的技术可用于数据分类,两种广泛使用的数据分类和降维技术是主成分分析(PCA)和线性判别分析(LDA)。人脸识别技术在电子商务领域得到了广泛的研究和应用。为了降低人脸识别过程中的误拒率(FRR)和误接受率(FAR),本文综述了影响人脸识别的方法和参数。此外,我们概述了这些技术的优势和挑战。这一综合性的研究可以作为每个有兴趣探索面部识别技术研究领域的人的起点和指南。本文给出了结论和今后的工作。
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