Abstract
As field of technology grows, security issues have gained high concern nowadays. Unfortunately, a good access authentication is high in price which had become less affordable. To overcome this scenario, Intelligent Door Locking System is proposed. This system can be divided into 3 parts, which are mobile application, server with web application and microcontroller. The mobile application will be the one in charge of having face recognition process. The face recognition will be carried out using Eigenfaces Algorithm. Users can lock the door using “Normal Lock” mode or “Secure Lock” mode. To unlock the “Normal Lock” mode, user just need to press on unlock button, while to unlock “Se- cure Lock” mode, user would need to pass biometric authentication and passcode authentication process. Once user successfully identified by the mobile application, data will be sent to microcontroller via Bluetooth. At the same time, the microcontroller will retrieve data from server database and check whether the user is having access to enter the room. If yes, the microcontroller will unlock the door. While for the server, it can be easily managed by administration using web application. Users can check their door lock condition from far distance through web application as well. They can lock the door if they realize the door is not locked wherever they are. This bring convenience to the user.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Soyata, T., Muraleedharan, R., Funai, C., Kwon, M., Heinzelman, W.: Cloud-vision: real-time face recognition using a mobile-cloudlet-cloud acceleration architecture. In: 2012 IEEE Symposium on Computers and Communications (ISCC), Cappadocia, pp. 59–66 (2012)
Januzaj, Y., Luma, A., Januzaj, Y., Ramaj, V.: Real time access control based on face recognition. In: 2015 International Conference on Network security & Computer Science, Antalya, Turkey, pp. 7–12 (2015)
Young, A.W., Burton, A.M.: Recognizing faces. Curr. Dir. Psychol. Sci. 26(3), 212–217 (2017)
Mesni, B.: Authentication in door access control systems. In: Clerk Maxwell, J. (ed.) A Treatise on Electricity and Magnetism, 3rd edn., vol. 2, pp. 68–73. Clarendon, Oxford (2013). http://kintronics.blogspot.my/2013/04/authentication-in-door-access-control.html
Joseph, J., Zacharia, K.P.: Automatic attendance management system using face recognition. Int. J. Sci. Res. (IJSR) 2(11), 327–330 (2013)
Turk, M.A., Pentland, A.P.: Face recognition using eigenfaces. In: Proceedings 1991 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 586–591 (1991)
Chintalapati, S., Raghunadh, M.V.: Automated attendance management system based on face recognition algorithms. In: 2013 IEEE International Conference on Computational Intelligence and Computing Research, Enathi, pp. 1–5 (2013)
Dave, G., Chao, X., Sriadibhatla, K.: Face recognition in mobile phones. Department of Electrical Engineering, Stanford University, Stanford, USA, pp. 1–7. https://stacks.stanford.edu/file/druid:rz261ds9725/Sriadibhatla_Davo_Chao_FaceRecognition.pdf
Saini, R., Saini, A., Agarwal, D.: Analysis of different face recognition algorithms. Int. J. Eng. Res. Technol. 3(11), 1263–1267 (2014)
Pabbaraju, A., Puchakayala, S.: Face recognition in mobile devices. Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, pp. 1–9 (2010). https://pdfs.semanticscholar.org/cc20/0b665f6c446747a48d01e89f6b1e7d7781d4.pdf
Mohamed, A.S.A.: Face recognition using eigenfaces. In: MRG International Conference 2006, Salford University, Manchester, United Kingdom, Poster Presentation (2006)
Turk, M., Pentland, A.: Eigenfaces for recognition. J. Cogn. Neurosci. 3(1), 71–86 (1991)
Belhumeur, P.N., Hespanha, J.P., Kriegman, D.J.: Eigenfaces vs. fisherfaces: recognition using class specific linear projection. IEEE Trans. Pattern Anal. Mach. Intell. 19(7), 711–719 (1997)
Karande, K.J., Talbar, S.N.: Simplified and modified approach for face recognition using PCA. IET-UK International Conference on Information and Communication Technology in Electrical Sciences (ICTES 2007), pp. 523–526. Dr. M.G.R. University, Chennai (2007)
Pissarenko, D.: Eigenface-based facial recognition (2003). http://openbio.sourceforge.net/resources/eigenfaces/eigenfaces-html/facesOptions.html
Zhao, W., Chellappa, R., Phillips, P.J., Rosenfeld, A.: Face recognition: a literature survey. ACM Comput. Surv. 35(4), 399–458 (2003)
Acknowledgement
This research is funded under USM RU Grant (PKOMP/8014001) and partly under USM Short Term Grant (PKOMP/6315262) and affiliated with Robotics, Computer Vision & Image Processing (RCVIP) Research Group Lab at School of Computer Sciences, Universiti Sains Malaysia.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Mohamed, A.S.A., Wahab, M.N.A., Krishnan, S.R., Arasu, D.B.L. (2019). Facial Recognition Adaptation as Biometric Authentication for Intelligent Door Locking System. In: Badioze Zaman, H., et al. Advances in Visual Informatics. IVIC 2019. Lecture Notes in Computer Science(), vol 11870. Springer, Cham. https://doi.org/10.1007/978-3-030-34032-2_24
Download citation
DOI: https://doi.org/10.1007/978-3-030-34032-2_24
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-34031-5
Online ISBN: 978-3-030-34032-2
eBook Packages: Computer ScienceComputer Science (R0)