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Improved Intuitive Automated Attendance System using Unorthodox Algorithms

by Prashant Wakchaure, Saad Shaikh, Kaushik Rohida, Sachita Singh, Ashish Ramdasi
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 177 - Number 9
Year of Publication: 2019
Authors: Prashant Wakchaure, Saad Shaikh, Kaushik Rohida, Sachita Singh, Ashish Ramdasi
10.5120/ijca2019919486

Prashant Wakchaure, Saad Shaikh, Kaushik Rohida, Sachita Singh, Ashish Ramdasi . Improved Intuitive Automated Attendance System using Unorthodox Algorithms. International Journal of Computer Applications. 177, 9 ( Oct 2019), 1-8. DOI=10.5120/ijca2019919486

@article{ 10.5120/ijca2019919486,
author = { Prashant Wakchaure, Saad Shaikh, Kaushik Rohida, Sachita Singh, Ashish Ramdasi },
title = { Improved Intuitive Automated Attendance System using Unorthodox Algorithms },
journal = { International Journal of Computer Applications },
issue_date = { Oct 2019 },
volume = { 177 },
number = { 9 },
month = { Oct },
year = { 2019 },
issn = { 0975-8887 },
pages = { 1-8 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume177/number9/30922-2019919486/ },
doi = { 10.5120/ijca2019919486 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:45:22.345232+05:30
%A Prashant Wakchaure
%A Saad Shaikh
%A Kaushik Rohida
%A Sachita Singh
%A Ashish Ramdasi
%T Improved Intuitive Automated Attendance System using Unorthodox Algorithms
%J International Journal of Computer Applications
%@ 0975-8887
%V 177
%N 9
%P 1-8
%D 2019
%I Foundation of Computer Science (FCS), NY, USA
Abstract

One of the troublesome undertakings in Image Processing is accurately recognizing faces in videos, which consecutively offers less precision. Recognizing faces irrespective of the gender is an effortless task for humans; however, from a machine or a robot’s perspective, it is an entangled task. Identifying the gender of an individual using their voice is simple when contrasted with facial pictures. This kind of binary classification can be used in various applications, for example, a surveillance system, directed publicizing, demographic gathering, human-machine interaction, content-based indexing and searching, biometrics, and so forth. In order to detect faces with ranging accuracy, there are multiple methods proposed by researchers, yet no existing system can produce an accuracy of 100%. In this manuscript, an automated attendance system is built, to recognize faces from existing trained dataset of student images collected from live training. Along with Face Recognition, the system is equipped with second-level security of QR code scanning. At the testing stage, the experimental results exhibited a precision of 93.00% and an f1-score of 0.9.

References
  1. Hamdi Dibekliolu, Fares Alnajar, Albert Ali Salah, Theo Gevers, Combining Facial Dynamics With Appearance for Age Estimation, IEEE Transactions on Image Processing, Volume: 24, Issue: 6, 1928 - 1943 (2015). doi:10.1109/TIP.2015.2412377.
  2. Yang Zhong, Josephine Sullivan, Haibo Li, Face attribute prediction using off-the-shelf CNN features, Paper presented at the 2016 International Conference on Biometrics (ICB), Halmstad, Sweden, 1 - 7 (2016). doi:10.1109/ICB.2016.7550092.
  3. Max Ehrlich, Timothy J. Shields, Timur Almaev, Mohamed R. Amer, Facial Attributes Classification Using Multi-task Representation Learning, Paper presented at the 2016 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW),Las Vegas, NV, USA, 752 - 760 (2016). doi:10.1109/CVPRW.2016.99.
  4. Jianlong Fu, Heliang Zheng, Tao Mei, Look Closer to See Better: Recurrent Attention Convolutional Neural Network for Fine-Grained Image Recognition, Paper presented at the 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR),Honolulu, HI, USA, 4476 - 4484 (2017). doi:10.1109/CVPR.2017.476.
  5. Yun-Fu Liu, Jing-Ming Guo, Po-Hsien Liu, Jiann-Der Lee, Chen-Chieh Yao, Panoramic Face Recognition, IEEE Transactions on Circuits and Systems for Video Technology, Volume: 28 , Issue: 8, 1864 - 1874 (2017). doi:10.1109/TCSVT.2017.2693682.
  6. Xiang-Yu Li, Zhen-Xian Lin, Face Recognition Based on HOG and Fast PCA Algorithm. In: Krmer P., Alba E., Pan JS., Sn?el V. (eds) Proceedings of the Fourth Euro-China Conference on Intelligent Data Analysis and Applications. ECC 2017. Advances in Intelligent Systems and Computing, vol 682. Springer, Cham, 10-21 (2017). doi:10.1007/978-3-319- 68527-4 2.
  7. Mashhood Sajid, Rubab Hussain, Muhammad Usman, A conceptual model for automated attendance marking system using facial recognition, Paper presented at the Ninth International Conference on Digital Information Management (ICDIM 2014), Phitsanulok, Thailand 7-10 (2014). doi:10.1109/ICDIM.2014.6991407.
  8. S Poornima, N Sripriya, B Vijayalakshmi, P Vishnupriya, Attendance monitoring system using facial recognition with audio output and gender classification, Paper presented at the 2017 International Conference on Computer Communication and Signal Processing (ICCCSP), Chennai, India, 1-5 (2017). doi:10.1109/ICCCSP.2017.7944103.
  9. Hemantkumar Rathod, Yudhisthir Ware, Snehal Sane, Suresh Raulo, Vishal Pakhare, Imdad A. Rizvi, Automated attendance system using machine learning approach, Paper presented at the 2017 International Conference on Nascent Technologies in Engineering (ICNTE), Navi Mumbai, India, 1-5 (2017). doi:10.1109/ICNTE.2017.7947889.
  10. Yueqi Duan, Jiwen Lu, Jianjiang Feng, Jie Zhou, Context- Aware Local Binary Feature Learning for Face Recognition, IEEE Transactions on Pattern Analysis and Machine Intelligence, Volume: 40 ,Issue: 5, 1139 - 1153 (2018). doi:10.1109/TPAMI.2017.2710183.
  11. Samuel Lukas, Aditya Rama Mitra, Ririn Ikana Desanti, Dion Krisnadi, Student attendance system in classroom using face recognition technique, Paper presented at the 2016 International Conference on Information and Communication Technology Convergence (ICTC), Jeju, South Korea, 1032 - 1035 (2016). doi:10.1109/ICTC.2016.7763360.
  12. Manop Phankokkruad, Phichaya Jaturawat, Influence of facial expression and viewpoint variations on face recognition accuracy by different face recognition algorithms, 2017 18th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Paper presented at the 2017 18th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/ Distributed Computing (SNPD), Kanazawa, Japan, 231 - 237 (2017). doi:10.1109/SNPD.2017.8022727.
  13. Hamdi Dibeklio?lu, Albert Ali Salah, Theo Gevers, Are You Really Smiling at Me? Spontaneous versus Posed Enjoyment Smiles. In: Fitzgibbon A., Lazebnik S., Perona P., Sato Y., Schmid C. (eds) Computer Vision ? ECCV 2012. ECCV 2012. Lecture Notes in Computer Science, vol 7574. Springer, Berlin, Heidelberg, 525-538 (2012). doi:10.1007/978-3-642- 33712-3 38.
  14. Ziwei Liu, Ping Luo, Xiaogang Wang, Xiaoou Tang, Deep Learning Face Attributes in the Wild, Paper presented at the 2015 IEEE International Conference on Computer Vision (ICCV), Santiago, Chile, 3730 - 3738 (2015). doi:10.1109/ICCV.2015.425.
  15. Shao-Dong Lv, Yong-Duan Song, Mei Xu, Cong-Ying Huang, Face Detection under Complex Background and Illumination, Journal of Electronic Science and Technology, 78- 82 (2015). doi:10.3969/j.issn.1674-862X.2015.01.014.
  16. Raghav Apoorv, Puja Mathur, Smart attendance management using Bluetooth Low Energy and Android, Paper presented at the 2016 IEEE Region 10 Conference (TENCON), Singapore, 1048 - 1052 (2016). doi:10.1109/TENCON.2016.7848166.
  17. M. K. Yeop, M. Z. A. Abdul Aziz, M. S. R. Mohd Shah, M. F. Abd Kadir, Smart Attendance System by using RFID, Paper presented at the 2007 Asia-Pacific Conference on Applied Electromagnetics, Melaka, Malaysia, 1 - 4 (2007). doi:10.1109/APACE.2007.4603906.
  18. M.A. Meor Said, M.H. Misran, M.A. Othman, M.M. Ismail, H.A. Sulaiman, A. Salleh, N. Yusop, Biometric attendance, Paper presented at the 2014 International Symposium on Technology Management and Emerging Technologies, Bandung, Indonesia, 258 - 263 (2014). doi:10.1109/ISTMET.2014.6936516.
  19. Fadi Masalha, Nael Hirzallah, A Students Attendance System Using QR Code, (IJACSA) International Journal of Advanced Computer Science and Applications, Vol. 5, No. 3, 75 - 79 (2014). doi:10.14569/issn.2156-5570.
  20. Prashant Wakchaure, Saad Shaikh, Sachita Singh, Kaushik Rohida, Prof Ashish Ramdasi, Literature Survey - Improved Intuitive Automated Attendance System Using Unorthodox Algorithms, INTERNATIONAL JOURNAL OF RESEARCH IN ELECTRONICS AND COMPUTER ENGINEERING (IJRECE), Vol.6, Issue: 4 (Version 5), 1480 - 1484 (2018). http://nebula. wsimg.com/911f286adcdcfe741d85aac5707541ca? AccessKeyId=DFB1BA3CED7E7997D5B1&disposition= 0&alloworigin=1
Index Terms

Computer Science
Information Sciences

Keywords

Face Recognition Images Haar-feature classifier face detection Support Vector Machine attendance QR Code f1-score Local binary Pattern

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