A review on face recognition systems: recent approaches and challenges
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A review on face recognition systems: recent approaches and challenges Muhtahir O. Oloyede 1,2 & Gerhard P. Hancke 2 & Hermanus C. Myburgh 2 Received: 8 August 2019 / Revised: 16 April 2020 / Accepted: 24 June 2020 # Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract
Face recognition is an efficient technique and one of the most preferred biometric modalities for the identification and verification of individuals as compared to voice, fingerprint, iris, retina eye scan, gait, ear and hand geometry. This has over the years necessitated researchers in both the academia and industry to come up with several face recognition techniques making it one of the most studied research area in computer vision. A major reason why it remains a fast-growing research lies in its application in unconstrained environments, where most existing techniques do not perform optimally. Such conditions include pose, illumination, ageing, occlusion, expression, plastic surgery and low resolution. In this paper, a critical review on the different issues of face recognition systems are presented, and different approaches to solving these issues are analyzed by presenting existing techniques that have been proposed in the literature. Furthermore, the major and challenging face datasets that consist of the different facial constraints which depict real-life scenarios are also discussed stating the shortcomings associated with them. Also, recognition performance on the different datasets by researchers are also reported. The paper is concluded, and directions for future works are highlighted. Keywords Face recognition . Biometrics . Techniques . Uncontrolled environment . Face dataset
1 Introduction Face recognition (FR) has over recent years been an active research area due to the various applications it can be applied, such as border security, surveillance, law enforcement and access control. Recently, other applications involved with the FR system include computer
* Muhtahir O. Oloyede [email protected]
1
Department of Information and Communication Science, University of Ilorin, Ilorin, Nigeria
2
Department of Electrical, Electronic and Computer Engineering, University of Pretoria, Pretoria, South Africa
Multimedia Tools and Applications
graphics, neural networks, and psychology as it is more of a multidisciplinary interest lately. Similar to other biometric systems, as shown in Fig. 1, the stages involved in the FR process are face detection, pre-processing of the face image, extraction of facial features and lastly feature classification [65]. The first stage which is the detection of the face is the process where the system is made to verify the presence of a face in an image or video. After detection of the face, the image is pre-processed to acquire the region of interest and also improve the image quality. Normalization is a type of pre-processing technique where the face images of different scales are transformed and mapped into the same scale. Face alignment is another preprocessing approach whi
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