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A survey of face recognition systems
Joint Authors
Abd Allah, Ihab Amir
Stephan, Jane Jalil
Source
Ibn al-Haitham Journal for Pure and Applied Science
Issue
Vol. 34, Issue 2 (30 Jun. 2021), pp.144-160, 17 p.
Publisher
University of Baghdad College of Education for Pure Science / Ibn al-Haitham
Publication Date
2021-06-30
Country of Publication
Iraq
No. of Pages
17
Main Subjects
Information Technology and Computer Science
Topics
- Image processing
- Neural networks(Computer science)
- Hidden Markov models
- Computer vision
- Facial expression
Abstract EN
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 re-searchers 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 tech-niques too, approaches: Hidden Markov Models, Principal Component Analysis (PCA), Elas-tic 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 Rob-ert Benavente) etc to analyze the results.
Even so, the goal of this survey is to present a com-prehensive literature review for the face recognition besides its applications after a deepness discussion, some of the experimental results was introduced in the 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 re-searchers 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 tech-niques too, approaches: Hidden Markov Models, Principal Component Analysis (PCA), Elas-tic 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 Rob-ert Benavente) etc to analyze the results.
Even so, the goal of this survey is to present a com-prehensive literature review for the face recognition besides its applications after a deepness discussion, some of the experimental results was introduced in the end.
American Psychological Association (APA)
Abd Allah, Ihab Amir& Stephan, Jane Jalil. 2021. A survey of face recognition systems. Ibn al-Haitham Journal for Pure and Applied Science،Vol. 34, no. 2, pp.144-160.
https://search.emarefa.net/detail/BIM-1255703
Modern Language Association (MLA)
Abd Allah, Ihab Amir& Stephan, Jane Jalil. A survey of face recognition systems. Ibn al-Haitham Journal for Pure and Applied Science Vol. 34, no. 2 (2021), pp.144-160.
https://search.emarefa.net/detail/BIM-1255703
American Medical Association (AMA)
Abd Allah, Ihab Amir& Stephan, Jane Jalil. A survey of face recognition systems. Ibn al-Haitham Journal for Pure and Applied Science. 2021. Vol. 34, no. 2, pp.144-160.
https://search.emarefa.net/detail/BIM-1255703
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 156-160
Record ID
BIM-1255703