AFRICAN JOURNAL OF COMMUNICATION AND LANGUAGE

Face alignment and normalization are the two irreplaceable foundations of the modern face recognition systems that cannot be assembled without prerequisite work. The purpose of these underlying processes is to canonicize the geometric arrangement as well as photographic look of facial images and to change extensively diverse, in-the-wild captures into a standard form that is amenable to dependable feature extraction and matching. This is the extensive paper that involves the in-depth analysis of the history, modern trends, and perspectives in the development of face alignment and normalization techniques. We begin with a clarification of their significant role in mitigating the adverse effect of the essential nuisance factors, such as pose, illumination, expression, and occlusion. The paper continues by giving a systematic taxonomy and a detailed discussion of fundamental methods, including the classical model- based methods such as Active Shape Models, the period of discriminative cascaded regression, and the modern model of deep learning-based holistic alignment and feature-level normalization networks. Much importance is taken on advanced and new issues: 3D-aware alignment to extreme pose correction, adversarial and disentangled representation learning to achieve photometric invariance, and the role of equitable normalization to reduce demographic bias in order to promote algorithmic fairness. More so, we consider how these modules can be strategically integrated into effective end-to-end recognition pipelines and optimized to execute on resource-constrained edge devices. This review summarizes the insights and findings of more than fifty publications that are regarded as seminal with an aim of formulating how advanced alignment and normalization have become more central than peripheral, of facilitating technologies. The development has played a crucial role in the transformation of face recognition as a limited laboratory use to a powerful and efficient biometric technology that can be able to function in the dynamic and challenging real world environment.