Survey Face Detection and Recognition

Abstract: In this paper we present a comprehensive and critical survey of face detection algorithms. Face detection is a necessary first-step in face recognition systems, with the purpose of localizing and extracting the face region from the background. It also has several applications in areas such as content-based image retrieval, video coding, video conferencing, crowd surveillance, and intelligent human–computer interfaces. However, it was not until recently that the face detection problem received considerable attention among researchers. The human face is a dynamic object and has a high degree of variability in its apperance, which makes face detection a difficult problem in computer vision. A wide variety of techniques have been proposed, ranging from simple edge-based algorithms to composite high-level approaches utilizing advanced pattern recognition methods. The algorithms presented in this paper are classified as either feature-based or image-based and are discussed in terms of their technical approach and performance. Due to the lack of standardized tests, we do not provide a comprehensive comparative evaluation, but in cases where results are reported on common datasets, comparisons are presented. We also give a presentation of some proposed applications and possible application areas.

Keywords: Classification, Face detection, Face recognition, Feature extraction, Preprocessing, Neural networks, Supports Vectors Machines (SVM).

Title: Survey Face Detection and Recognition

Author: Noor Shakir Hameed

International Journal of Novel Research in Computer Science and Software Engineering

ISSN 2394-7314

Vol. 10, Issue 1, January 2023 - April 2023

Page No: 1-7

Novelty Journals

Website: www.noveltyjournals.com

Published Date: 13-January-2023

DOI: https://doi.org/10.5281/zenodo.7534129

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