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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