SAFE: Security Door Lock System Using Haar-Cascade and LBPH Method

Research Article
Open access

SAFE: Security Door Lock System Using Haar-Cascade and LBPH Method

Jing-Han Leim 1* , Kok-Why Ng 2 , Arpitha S. 3 , Sew-Lai Ng 4 , Su-Cheng Haw 5
  • 1 Faculty of Computing and Informatics, Multimedia University, Malaysia    
  • 2 Faculty of Computing and Informatics, Multimedia University, Malaysia    
  • 3 Faculty of Computing and Informatics, Multimedia University, Malaysia    
  • 4 Faculty of Computing and Informatics, Multimedia University, Malaysia    
  • 5 Faculty of Computing and Informatics, Multimedia University, Malaysia    
  • *corresponding author kwng@mmu.edu.my
Published on 22 March 2023 | https://doi.org/10.54254/2755-2721/2/20220646
ACE Vol.2
ISSN (Print): 2755-273X
ISSN (Online): 2755-2721
ISBN (Print): 978-1-915371-19-5
ISBN (Online): 978-1-915371-20-1

Abstract

Door lock provides numerous benefits and has become indispensable in daily life as it acts as a security guard to prevent burglars and protect home belonging safely. The unlock methods of existing door lock system widely use keys and thumbprint involve touching the object may cause the spread of COVID-19. In this paper, a computer vision based security door lock system using Raspberry Pi (called SAFE) is proposed. Haar-Cascade classifier is employed as face detection classifier, while Local Binary Pattern Histogram (LBPH) is proposed as face recognition classifier. Recognition result is processed based on the usage of user to provide insights of SAFE. The accuracy of SAFE using pre-trained LBPH classifier achieves average of 86% based on the data obtained. The recognition speed outperforms existing work using principal component analysis and eigenfaces.

Keywords:

Door Lock System., Raspberry Pi, Haar Cascade

Leim,J.;Ng,K.;S.,A.;Ng,S.;Haw,S. (2023). SAFE: Security Door Lock System Using Haar-Cascade and LBPH Method. Applied and Computational Engineering,2,802-810.
Export citation

References

[1]. Wazwaz, A. A., Herbawi, A. O., Teeti, M. J., Hmeed, S. Y. Raspberry Pi and computers-based face detection and recognition system. In: 2018 4th International Conference on Computer and Technology Applications (ICCTA), pp. 171-174. IEEE (2018).

[2]. Park, Y. T., Sthapit, P., Pyun, J. Y. Smart digital door lock for the home automation. In: TENCON 2009-2009 IEEE Region 10 Conference (pp. 1-6). IEEE (2009).

[3]. Prity, S. A., Afrose, J., Hasan, M. RFID Based Smart Door Lock Security System. American Journal of Sciences and Engineering Research E-ISSN-2348-703X, 4(3) (2021).

[4]. Baidya, J., Saha, T., Moyashir, R., Palit, R. Design and implementation of a fingerprint based lock system for shared access. In: 2017 IEEE 7th Annual Computing and Communication Workshop and Conference (CCWC) (pp. 1-6). IEEE (2017).

[5]. Alghamdi and Abdullah, Security Lock systems: From Problem Statement to System Design Name of the Author, 2020. DOI:10.13140/RG.2.2.19174.04163

[6]. Nag, A., Nikhilendra, J. N., Kalmath, M. IOT based door access control using face recognition. In: 3rd International Conference for Convergence in Technology (I2CT), pp. 1-3. IEEE (2018).

[7]. Azriansyah, M., Hartuti, N., Fachrurrozi, M., Tama, B. A. A study about principle component analysis and eigenface for facial extraction. In: Journal of Physics: Conference Series 1196(1), pp. 012010. IOP Publishing (2019).

[8]. Lwin, H. H., Khaing, A. S., Tun, H. M. Automatic door access system using face recognition. International Journal of scientific & technology research, 4(6), pp. 294-299 (2015).

[9]. Faisal, F., Hossain, S. A. Smart security system using face recognition on raspberry pi. In: 2019 13th International Conference on Software, Knowledge, Information Management and Applications (SKIMA), pp. 1-8. IEEE (2019).

[10]. Gunawan, T. S., Gani, M. H. H., Rahman, F. D. A., Kartiwi, M. Development of face recogni-tion on raspberry pi for security enhancement of smart home system. Indonesian Journal of Electrical Engineering and Informatics (IJEEI), 5(4), pp. 317-325 (2017).

[11]. Manjunatha, R., Nagaraja, R. Home security system and door access control based on face recognition. International Research Journal of Engineering and Technology (IRJET), 4(03), pp. 2395-0056 (2017).

[12]. Rizki, R. P., Hamidi, E. A. Z., Kamelia, L., Sururie, R. W. Image Processing Technique for Smart Home Security Based On the Principal Component Analysis (PCA) Methods. In: 6th International Conference on Wireless and Telematics (ICWT), pp. 1-4. IEEE (2020).

[13]. Jahnavi, S., Nandini, C. Smart Anti-Theft Door locking System. In: 1st International Confer-ence on Advanced Technologies in Intelligent Control, Environment, Computing & Com-munication Engineering (ICATIECE), pp. 205-208. IEEE (2019).

[14]. Vamsi, T., Sai, K. C., Vijayalakshmi, M. Face recognition based door unlocking system using Raspberry Pi. International Journal of Advanced Research, Ideas and Innovation in Tech-nology (2019).

[15]. Khan, M. A., Shaikh, M. K., bin Mazhar, S. A., Mehboob, K. Comparative analysis for a real time face recognition system using raspberry Pi. In 2017 IEEE 4th International Conference on Smart Instrumentation, Measurement and Application (ICSIMA), pp. 1-4. IEEE (2017).

[16]. Pawar, S., Kithani, V., Ahuja, S., Sahu, S. Smart home security using IoT and face recognition. In 2018 Fourth International Conference on Computing Communication Control and Auto-mation (ICCUBEA), pp. 1-6. IEEE (2018).

[17]. R. Ganjoo, A. Purohit. Anti-Spoofing Door Lock Using Face Recognition and Blink Detection. 6th International Conference on Inventive Computation Technologies (ICICT), 2021, pp. 1090-1096 (2021). doi: 10.1109/ICICT50816.2021.9358795.

[18]. Yawalikar, Apurva Hore, Security Implementation by Machine Learning Based Face Recog-nization with SVM (2021). DOI:10.48175/IJARSCT-975

[19]. Cindori, D., Tomičić, I., Grd, P. Security Hardening of Facial Recognition Systems. In 44th International Convention on Information, Communication and Electronic Technology (MIPRO), pp. 1015-1019. IEEE (2021).

[20]. Coşkun, Romit Purohit, Anjali, International Conference on Modern Electrical and Energy Systems (MEES) (2017).

[21]. Ong, K., Haw, S. C., Ng, K. W. Deep Learning Based-Recommendation System: An Over-view on Models, Datasets, Evaluation Metrics, and Future Trends. In: 2nd International Conference on Computational Intelligence and Intelligent Systems, pp. 6-11 (2019).

[22]. Ang, J. S., Ng, K. W., Chua, F. F.. Modeling Time Series Data with Deep Learning: A Re-view, Analysis, Evaluation and Future Trend. In: 8th International Conference on Infor-mation Technology and Multimedia (ICIMU), pp. 32-37. IEEE (2020).

[23]. MaYing, M., Kim, K. C. CNN Based 2D and 2.5 D Face Recognition For Home Security Sys-tem. The Journal of the Korea institute of electronic communication sciences, 14(6), pp. 1207-1214 (2019).

[24]. Uetama, T. R., Setiawan, W., Sofyan, E. Performance comparation of real time image pro-cessing face recognition for security system. In: Proceedings of The Conference on Man-agement and Engineering in Industry 2(1), pp. 21-25 (2020).

[25]. Mishra, R., Ransingh, A., Behera, M. K., Chakravarty, S. Convolutional Neural Network Based Smart Door Lock System. In: India Council International Subsections Conference (INDISCON), pp. 151-156. IEEE (2020).

[26]. Irjanto, N. S., Surantha, N. Home Security System with Face Recognition based on Convolu-tional Neural Network. (IJACSA) International Journal of Advanced Computer Science and Applications, 11(11) (2020).

Cite this article

Leim,J.;Ng,K.;S.,A.;Ng,S.;Haw,S. (2023). SAFE: Security Door Lock System Using Haar-Cascade and LBPH Method. Applied and Computational Engineering,2,802-810.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

Disclaimer/Publisher's Note

The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of EWA Publishing and/or the editor(s). EWA Publishing and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

About volume

Volume title: Proceedings of the 4th International Conference on Computing and Data Science (CONF-CDS 2022)

ISBN：978-1-915371-19-5(Print) / 978-1-915371-20-1(Online)
Editor：Alan Wang
Conference website: https://www.confcds.org/
Conference date: 16 July 2022
Series: Applied and Computational Engineering
Volume number: Vol.2
ISSN：2755-2721(Print) / 2755-273X(Online)

© 2024 by the author(s). Licensee EWA Publishing, Oxford, UK. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license. Authors who publish this series agree to the following terms:
1. Authors retain copyright and grant the series right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this series.
2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the series's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this series.
3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See Open access policy for details).

References

[1]. Wazwaz, A. A., Herbawi, A. O., Teeti, M. J., Hmeed, S. Y. Raspberry Pi and computers-based face detection and recognition system. In: 2018 4th International Conference on Computer and Technology Applications (ICCTA), pp. 171-174. IEEE (2018).

[2]. Park, Y. T., Sthapit, P., Pyun, J. Y. Smart digital door lock for the home automation. In: TENCON 2009-2009 IEEE Region 10 Conference (pp. 1-6). IEEE (2009).

[3]. Prity, S. A., Afrose, J., Hasan, M. RFID Based Smart Door Lock Security System. American Journal of Sciences and Engineering Research E-ISSN-2348-703X, 4(3) (2021).

[4]. Baidya, J., Saha, T., Moyashir, R., Palit, R. Design and implementation of a fingerprint based lock system for shared access. In: 2017 IEEE 7th Annual Computing and Communication Workshop and Conference (CCWC) (pp. 1-6). IEEE (2017).

[5]. Alghamdi and Abdullah, Security Lock systems: From Problem Statement to System Design Name of the Author, 2020. DOI:10.13140/RG.2.2.19174.04163

[6]. Nag, A., Nikhilendra, J. N., Kalmath, M. IOT based door access control using face recognition. In: 3rd International Conference for Convergence in Technology (I2CT), pp. 1-3. IEEE (2018).

[7]. Azriansyah, M., Hartuti, N., Fachrurrozi, M., Tama, B. A. A study about principle component analysis and eigenface for facial extraction. In: Journal of Physics: Conference Series 1196(1), pp. 012010. IOP Publishing (2019).

[8]. Lwin, H. H., Khaing, A. S., Tun, H. M. Automatic door access system using face recognition. International Journal of scientific & technology research, 4(6), pp. 294-299 (2015).

[9]. Faisal, F., Hossain, S. A. Smart security system using face recognition on raspberry pi. In: 2019 13th International Conference on Software, Knowledge, Information Management and Applications (SKIMA), pp. 1-8. IEEE (2019).

[10]. Gunawan, T. S., Gani, M. H. H., Rahman, F. D. A., Kartiwi, M. Development of face recogni-tion on raspberry pi for security enhancement of smart home system. Indonesian Journal of Electrical Engineering and Informatics (IJEEI), 5(4), pp. 317-325 (2017).

[11]. Manjunatha, R., Nagaraja, R. Home security system and door access control based on face recognition. International Research Journal of Engineering and Technology (IRJET), 4(03), pp. 2395-0056 (2017).

[12]. Rizki, R. P., Hamidi, E. A. Z., Kamelia, L., Sururie, R. W. Image Processing Technique for Smart Home Security Based On the Principal Component Analysis (PCA) Methods. In: 6th International Conference on Wireless and Telematics (ICWT), pp. 1-4. IEEE (2020).

[13]. Jahnavi, S., Nandini, C. Smart Anti-Theft Door locking System. In: 1st International Confer-ence on Advanced Technologies in Intelligent Control, Environment, Computing & Com-munication Engineering (ICATIECE), pp. 205-208. IEEE (2019).

[14]. Vamsi, T., Sai, K. C., Vijayalakshmi, M. Face recognition based door unlocking system using Raspberry Pi. International Journal of Advanced Research, Ideas and Innovation in Tech-nology (2019).

[15]. Khan, M. A., Shaikh, M. K., bin Mazhar, S. A., Mehboob, K. Comparative analysis for a real time face recognition system using raspberry Pi. In 2017 IEEE 4th International Conference on Smart Instrumentation, Measurement and Application (ICSIMA), pp. 1-4. IEEE (2017).

[16]. Pawar, S., Kithani, V., Ahuja, S., Sahu, S. Smart home security using IoT and face recognition. In 2018 Fourth International Conference on Computing Communication Control and Auto-mation (ICCUBEA), pp. 1-6. IEEE (2018).

[17]. R. Ganjoo, A. Purohit. Anti-Spoofing Door Lock Using Face Recognition and Blink Detection. 6th International Conference on Inventive Computation Technologies (ICICT), 2021, pp. 1090-1096 (2021). doi: 10.1109/ICICT50816.2021.9358795.

[18]. Yawalikar, Apurva Hore, Security Implementation by Machine Learning Based Face Recog-nization with SVM (2021). DOI:10.48175/IJARSCT-975

[19]. Cindori, D., Tomičić, I., Grd, P. Security Hardening of Facial Recognition Systems. In 44th International Convention on Information, Communication and Electronic Technology (MIPRO), pp. 1015-1019. IEEE (2021).

[20]. Coşkun, Romit Purohit, Anjali, International Conference on Modern Electrical and Energy Systems (MEES) (2017).

[21]. Ong, K., Haw, S. C., Ng, K. W. Deep Learning Based-Recommendation System: An Over-view on Models, Datasets, Evaluation Metrics, and Future Trends. In: 2nd International Conference on Computational Intelligence and Intelligent Systems, pp. 6-11 (2019).

[22]. Ang, J. S., Ng, K. W., Chua, F. F.. Modeling Time Series Data with Deep Learning: A Re-view, Analysis, Evaluation and Future Trend. In: 8th International Conference on Infor-mation Technology and Multimedia (ICIMU), pp. 32-37. IEEE (2020).

[23]. MaYing, M., Kim, K. C. CNN Based 2D and 2.5 D Face Recognition For Home Security Sys-tem. The Journal of the Korea institute of electronic communication sciences, 14(6), pp. 1207-1214 (2019).

[24]. Uetama, T. R., Setiawan, W., Sofyan, E. Performance comparation of real time image pro-cessing face recognition for security system. In: Proceedings of The Conference on Man-agement and Engineering in Industry 2(1), pp. 21-25 (2020).

[25]. Mishra, R., Ransingh, A., Behera, M. K., Chakravarty, S. Convolutional Neural Network Based Smart Door Lock System. In: India Council International Subsections Conference (INDISCON), pp. 151-156. IEEE (2020).

[26]. Irjanto, N. S., Surantha, N. Home Security System with Face Recognition based on Convolu-tional Neural Network. (IJACSA) International Journal of Advanced Computer Science and Applications, 11(11) (2020).

For authors
Guide for authors Policies for authors Aims and scope Subscription Open access policy
For editors
Policies for editors Editorial board
For reviewers
Policies for reviewers Privacy policy

Cookies are used by this site.
Copyright © 2024 EWA Publishing, its licensors, and contributors. All rights reserved, including text and data mining, AI training, and similar technologies.