A SYSTEM FOR MANAGING ATTENDANCE OF ACADEMIC STAFF MEMBERS IN UNIVERSITY DEVELOPMENT PROGRAMS USING FACE RECOGNITION | ||
| International Journal of Intelligent Computing and Information Sciences | ||
| Article 1, Volume 17, Issue 4, October 2017, Pages 1-17 PDF (1.36 M) | ||
| Document Type: Original Article | ||
| DOI: 10.21608/ijicis.2018.7706 | ||
| Author | ||
| Wessam ElSaid | ||
| Department of Computer Teacher Prepration, Faculty of Specific Education, Mansoura University, Mansoura, Egypt | ||
| Abstract | ||
| great development in all aspects of the life imposes new changes on various organizations. Since the academic institutions are not isolated from the real world events, they have sought to build an integrated strategy for developing their activities and services to keep pace with the new reality. One of the major development areas in the university sector is the improvement of the academic staff members’ skills on both the leadership and academic levels through a series of certified development programs. Until now, recording the members’ attendance in these programs depends on traditional manual methods which have many drawbacks. Therefore, the current study presents an automatic system based on face recognition technology to address these drawbacks.The proposed system includes five main steps: capturing member image, detecting member face, extracting facial features, comparing facial features and creating target reports. The system usefulness can be viewed form two major aspects.Aspect-1; is the accuracy rate in which proposed system achieved significant performance under ideal imaging conditions and achieved acceptable performance under un-ideal imaging conditions compared with some other systems in the same field. Aspect-2; is the cost rate in which the proposed system does not require an expensive settings, making it an appropriate choice for various educational institutions. | ||
| Keywords | ||
| Educational Institutions; Academic Staff Members; Development Programs; Managing Attendance; Face Recognition; Haar Cascade Classifier; Local Binary Pattern | ||
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