Journal of Information Systems Engineering and Management

Using Technology and Algorithms for Face Detection and Recognition Using Digital Image Processing and Relying on a Computer Vision Sensor
Rasha Basim Yousif Al-khafaji 1 *
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1 Lecturer, Department of Computer Science, College of Computer Science and Mathematics, University of Thi-Qar, Nasiriyah, Iraq
* Corresponding Author
Research Article

Journal of Information Systems Engineering and Management, 2024 - Volume 9 Issue 1, Article No: 25018
https://doi.org/10.55267/iadt.07.14328

Published Online: 29 Jan 2024

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How to cite this article
APA 6th edition
In-text citation: (Al-khafaji, 2024)
Reference: Al-khafaji, R. B. Y. (2024). Using Technology and Algorithms for Face Detection and Recognition Using Digital Image Processing and Relying on a Computer Vision Sensor. Journal of Information Systems Engineering and Management, 9(1), 25018. https://doi.org/10.55267/iadt.07.14328
Vancouver
In-text citation: (1), (2), (3), etc.
Reference: Al-khafaji RBY. Using Technology and Algorithms for Face Detection and Recognition Using Digital Image Processing and Relying on a Computer Vision Sensor. J INFORM SYSTEMS ENG. 2024;9(1):25018. https://doi.org/10.55267/iadt.07.14328
AMA 10th edition
In-text citation: (1), (2), (3), etc.
Reference: Al-khafaji RBY. Using Technology and Algorithms for Face Detection and Recognition Using Digital Image Processing and Relying on a Computer Vision Sensor. J INFORM SYSTEMS ENG. 2024;9(1), 25018. https://doi.org/10.55267/iadt.07.14328
Chicago
In-text citation: (Al-khafaji, 2024)
Reference: Al-khafaji, Rasha Basim Yousif. "Using Technology and Algorithms for Face Detection and Recognition Using Digital Image Processing and Relying on a Computer Vision Sensor". Journal of Information Systems Engineering and Management 2024 9 no. 1 (2024): 25018. https://doi.org/10.55267/iadt.07.14328
Harvard
In-text citation: (Al-khafaji, 2024)
Reference: Al-khafaji, R. B. Y. (2024). Using Technology and Algorithms for Face Detection and Recognition Using Digital Image Processing and Relying on a Computer Vision Sensor. Journal of Information Systems Engineering and Management, 9(1), 25018. https://doi.org/10.55267/iadt.07.14328
MLA
In-text citation: (Al-khafaji, 2024)
Reference: Al-khafaji, Rasha Basim Yousif "Using Technology and Algorithms for Face Detection and Recognition Using Digital Image Processing and Relying on a Computer Vision Sensor". Journal of Information Systems Engineering and Management, vol. 9, no. 1, 2024, 25018. https://doi.org/10.55267/iadt.07.14328
ABSTRACT
Advancing in variable scopes in network technology, many new technologies were developed. Security issues were important, especially in the detection and recognition of people using variable methods like face details. Sensors have been used widely in recent days to support security systems. Sensors are devices used to convert any type of signals into electrical signals that are recorded to be processed later. These signals can be viewed by the user in several ways. Sensors increased in the development stage that can be integrated with operating systems, data storage systems, processing units, communication units, and any other function units. Detection and recognition systems were developed into a new level of technology. Some systems like figure print and palm lines face many problems because the possible change of the skin structure can be faced in time. So, these methods faced a certain problem and limitations that caused them to search for other methods more accurate. This search aims to create a new method for face detection and recognition depending on sensors. Most of the methods used for face recognition depend on OpenCV libraries that give good accuracy and time recovery availability. On the other hand, practical applications were developed to increase the accuracy of these systems like SeetaFace and YouTu methods. Three methods of detection were important to be detected too to increase the accuracy of the whole system which are the side face detection, the occlusion detection, and the face expressions. Then these data were compared to create the whole accuracy result of the system.
KEYWORDS
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