International Journal of Computer Science & Network Security

International Journal of Computer Science & Network Security (국제컴퓨터통신보호논문지학회)
권호 표지
DOI QR코드

DOI QR Code

Face Recognition Using a Facial Recognition System

  • Almurayziq, Tariq S (Department of Information and Computer Science, College of Computer Science and Engineering, University of Ha'il) ;
  • Alazani, Abdullah (Department of Information and Computer Science, College of Computer Science and Engineering, University of Ha'il)
  • Received : 2022.09.05
  • Published : 2022.09.30
Download PDF
⟨ Previous Next ⟩

Abstract

Facial recognition system is a biometric manipulation. Its applicability is simpler, and its work range is broader than fingerprints, iris scans, signatures, etc. The system utilizes two technologies, such as face detection and recognition. This study aims to develop a facial recognition system to recognize person's faces. Facial recognition system can map facial characteristics from photos or videos and compare the information with a given facial database to find a match, which helps identify a face. The proposed system can assist in face recognition. The developed system records several images, processes recorded images, checks for any match in the database, and returns the result. The developed technology can recognize multiple faces in live recordings.

Keywords

References

  1. Lin, S.-H.: An Introduction to Face Recognition Technology. Informing Science (Multimedia Informing Technologies) 3(1), 7 (2000).
  2. Virmani, D., Girdhar, P., Jain, P., Bamdev, P.: FDREnet: Face Detection and Recognition Pipeline. Engineering, Technology & Applied Science Research 9(2), 3933-3938 (2019). https://doi.org/10.48084/etasr.2492
  3. Salamh, A. B. S., Akyuz, H. I.: A Novel Feature Extraction Descriptor for Face Recognition. Engineering, Technology & Applied Science Research 12(1), 8033-8038 (2022). https://doi.org/10.48084/etasr.4624
  4. Zhou, L., Wang, H., Liu, W., Lu, Z.-M.: Face Feature Extraction and Recognition via Local Binary Pattern and Two-dimensional Locality Preserving Projection. Multimedia Tools and Applications 78(11), 14971-14987 (2019). https://doi.org/10.1007/s11042-018-6868-6
  5. Gurel, C., Erden, A.: Design of a Face Recognition System. In: 15th International Conference on Machine Design and Production (UMTIK), pp. 1-12 (2012).
  6. Alamri, H., Alshanbari, E., Alotaibi, S., Alghamdi, M.: Face Recognition and Gender Detection Using SIFT Feature Extraction, LBPH, and SVM. Engineering, Technology & Applied Science Research 12(2), 8296-8299 (2022). https://doi.org/10.48084/etasr.4735
  7. Hassaballah, M., Aly, S.: Face Recognition: Challenges, Achievements and Future Directions. IET Computer Vision 9(4), 614-626 (2015). https://doi.org/10.1049/iet-cvi.2014.0084
  8. Kar, N., Debbarma, M. K., Saha, A., Pal, D. R.: Study of Implementing Automated Attendance System Using Face Recognition Technique. International Journal of Computer and Communication Engineering 1(2), 100-103 (2012).
  9. Pato, J. N., Millett, L. I.: Biometric Recognition: Challenges and Opportunities. Washington, DC, USA: The National Academies Press pp. 182 (2010).
  10. Kelly, M. D.: Visual Identification of People by Computer. Ph.D. dissertation, Dept. of Computer Science, Stanford University, Stanford, CA, USA (1970).
  11. Zhang, J., Yan, Y., Lades, M.: Face Recognition: Eigenface, Elastic Matching, and Neural Nets. Proceedings of the IEEE 85(9), 1423-1435 (1997). https://doi.org/10.1109/5.628712
  12. Chellappa, R., Wilson, C. L., Sirohey, S.: Human and Machine Recognition of Faces: A Survey. Proceedings of the IEEE 83(5), 705-741 (1995). https://doi.org/10.1109/5.381842
  13. Kortli, Y., Jridi, M., Al Falou, A., Atri, M.: Face Recognition Systems: A Survey. Sensors 20(2), 342 (2020).
  14. Said, Y., Barr, M., Ahmed, H. E.: Design of a Face Recognition System Based on Convolutional Neural Network (CNN). Engineering, Technology & Applied Science Research 10(3), 5608-5612 (2020). https://doi.org/10.48084/etasr.3490
  15. Mordor Intelligence: Facial Recognition Market - Growth, Trends, COVID-19 Impact, and Forecasts (2022-2027). https://www.mordorintelligence.com/industryreports/facial-recognition-market (accessed July 21, 2020).
  16. Panchabhaiya, V. (2019): Real-Time Face Detection Using MATLAB. https://www.electronicsforu.com/electronicsprojects/software-projects-ideas/real-time-face-detectionusing-matlab (accessed July 2020).
  17. Duchaine B., Yovel, G.: Face Recognition: in The Senses: A Comprehensive Reference. Elsevier 2, 329-357 (2008).
  18. Vishwakarma, V. P., Goel, T.: An Efficient Hybrid DWTFuzzy Filter in DCT Domain Based Illumination Normalization for Face Recognition. Multimedia Tools Application 78(11), 15213-15233 (2019). https://doi.org/10.1007/s11042-018-6837-0
  19. AT&T Database of Faces: ORL Face Database. http://camorl.co.uk/facedatabase.html (accessed July 21, 2020).
  20. Lowe, D. G.: Distinctive Image Features from ScaleInvariant Keypoints. International Journal of Computer Vision 60(2), 91-110 (2004). https://doi.org/10.1023/B:VISI.0000029664.99615.94
  21. Diyasa, G. S. M., Fauzi, A., Idhom, M., Setiawan, A.: Multiface Recognition for the Detection of Prisoners in Jail using a Modified Cascade Classifier and CNN. Journal of Physics: Conference Series 1844, 012005 (2021).