A Survey of Face Recognition Systems

Main Article Content

Ihab Amer Abdullah Jane Jaleel Stephan

Abstract

With the quick grow of multimedia contents, from among this content, face recognition has got a lot of significant, specifically in latest little years. The face as object formed of various recognition characteristics for detect; so, it is still the most challenge research domain for researchers in area of image processing and computer vision. In this survey article, tried to solve the most demanding facial features like illuminations, aging, pose variation, partial occlusion and facial expression. Therefore, it indispensable factors in the system of facial recognition when performed on facial pictures. This paper study the most advanced facial detection techniques too, approaches: Hidden Markov Models, Principal Component Analysis (PCA), Elastic Cluster Plot Matching, Support Vector Machines (SVM), Gabor Waves, Artificial Neural Networks (ANN), Eigen Face, Independent Component Analysis (ICA) and 3D Morphable Model. Additionally to the above works, mentioned various testing facial databases including JAFEE, FEI, Yale, LFW, AT&T(formerly termed as ORL) and AR (Aleix Martinez and Robert Benavente) etc to analyze the results. Even so, the goal of this survey is to present a comprehensive literature review for the face recognition besides its applications after a deepness discussion, some of the experimental results was introduced in the end.

Article Details

How to Cite
ABDULLAH, Ihab Amer; STEPHAN, Jane Jaleel. A Survey of Face Recognition Systems. Ibn AL- Haitham Journal For Pure and Applied Science, [S.l.], v. 34, n. 2, p. 144-160, apr. 2021. ISSN 2521-3407. Available at: <https://jih.uobaghdad.edu.iq/index.php/j/article/view/2620>. Date accessed: 31 july 2021.
Section
computer