Facial Detection and Recognition using Efficient Features for Enhanced Security Systems
Sana Zahir, Institute of Computer Sciences and Information Technology (ICS/IT), The University of Agriculture Peshawar, Pakistan.
Arbab Waseem Abbas, Institute of Computer Sciences and Information Technology (ICS/IT), The University of Agriculture Peshawar, Pakistan.
Muhammad Ishaq, Institute of Computer Sciences and Information Technology (ICS/IT), The University of Agriculture Peshawar, Pakistan.
Iqtidar Ali, Institute of Computer Sciences and Information Technology (ICS/IT), The University of Agriculture Peshawar, Pakistan.
Lala Rukh, Institute of Computer Sciences and Information Technology (ICS/IT), The University of Agriculture Peshawar, Pakistan.
Afaq Amin Khan, Institute of Computer Sciences and Information Technology (ICS/IT), The University of Agriculture Peshawar, Pakistan.
Corresponding Author:
Sana Zahir (sanakhan131s@gmail.com)
Abstract:
The motivation behind security surveillance systems is to ensure the safety and security of people and property. These systems provide a way to monitor and detect potential threats and take necessary action. In this paper, we proposed a face detection and recognition system to enhance the efficiency and accuracy of security surveillance systems. The paper introduces a coverage model consisting of two modules - face recognition and face detection - optimized to achieve the best surveillance of the task area. The controlling and face-following algorithm is also developed. The coverage strength model is applied to reduce the hardware requirements and time needed to achieve good results. This study provides valuable insights into improving the efficiency of security surveillance systems. The system achieved 82% recognition rate for indoor scenes under ideal conditions like full light, while the outdoor experiment reached a saturation point of 77% due to the system's limitations in long-range detection.
Keywords:
Face Detection; Face Recognition; Security System; Image Processing