Copyright: © the author(s), publisher and licensee Technoscience Academy. This is an open-access article distributed under the terms of the Creative Commons Attribution Non-Commercial License, which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited International Journal of Scientific Research in Computer Science, Engineering and Information Technology ISSN : 2456-3307 (www.ijsrcseit.com) https://doi.org/10.32628/CSEIT21762 57 A Survey on Classical and Modern Face Recognition Techniques M. ShalimaSulthana 1 , C. Naga Raju 2 1 Research Scholar, Department of Computer Science and Engineering, YSR Engineering College of YVU Yogivemana University-Kadapa, Andhra Pradesh, India 2 Professor, Department of Computer Science and Engineering, YSR Engineering College of YVU, Yogivemana University-Kadapa, Andhra Pradesh, India Article Info Volume 7, Issue 6 Page Number: 57-79 Publication Issue : November-December-2021 Article History Accepted : 08 Nov 2021 Published : 19 Nov 2021 ABSTRACT During the previous few centuries, facial recognition systems have become a popular research topic. On account of its extraordinary success and vast social applications; it has attracted significant study attention from a wide range of disciplines in the last five years - including “computer-vision”, “artificial- intelligence”, and “machine-learning”. As with most face recognition systems, the fundamental goal involves recognizing a person's identity by means of images, video, data streams, and context information. As a result of our research; we've outlined some of the most important applications, difficulties, and trends in scientific and social domains. This research, the primary goal is to summarize modern facial recognition algorithms and to gain a general perceptive of how these techniques act on diverse datasets. Aside from that, we also explore some significant problems like illumination variation, position, aging, occlusion, cosmetics, scale, and background are some of the primary challenges we examine. In addition to traditional face recognition approaches, the most recent research topics such as sparse models, deep learning, and fuzzy set theory are examined in depth. There's also a quick discussion of basic techniques, as well as a more in-depth. As a final point, this research explores the future of facial recognition technologies and their possible importance in the emerging digital society. I. INTRODUCTION The term “Face recognition research” has become extremely popular over the last few decades and it has a wide variety of scientific, social, and business applications. Face recognition has been major prominent research areas in “image processing”, “machine learning”, “computer vision”, “artificial intelligence” and “visual surveillance” in the last five years. Face recognition systems must be able to determine a person's identity from static photos [1], video data [2] or data streams [3] in order to be effective. A broad definition of face recognition encompasses a variety of technologies that can be used to create a facial recognition system. Image preprocessing and