2771-1463ISSN (Online)
2771-1471ISSN (Print)
Volume 2 , Issue 1 , PP: 15-18, 2022 | Cite this article as | XML | Html | PDF | Full Length Article
Sumithra.M 1 , Vettri Chezhian. P 2 , Raj Kumar. K 3 , Nithish Kumar. S 4
Doi: https://doi.org/10.54216/JCHCI.020102
This project aims to design a automated attendance system using face-recognition and MySQL database. We have presented our idea to implement an “Automated Attendance System Using Real Time Face recognition and MySQL Database”. The application includes face identification, which saves time as well as being purely software based it can be flagged as eco-friendly as it reduces the use of paper and also send a message to the student of his attendance record in the end of every day. This system also eliminates the chances of fake attendance because of the face being used as a biometric for authentication. This system avoids the concept of fake attendance where attendance plays an important role. The proposed system is designed in Python as well as SQL database. The algorithm used in the system compare the image captured encoded value with the value already available with us to recognize the face. The system has output in the form of MYSQL Database.
Eco-friendly, Automated time tracking system, No manual work done.
[1] Agrawal, S., Khatri, P.: Facial expression detection techniques: based on Viola and Jones algorithm and
principal component analysis. In: 2015 Fifth International Conference on Advanced Computing &
Communication Technologies, pp. 108–112.IEEE (2015).
[2] Ahmedi, A., Nandyal, S.: An automatic attendance system using image processing.Int. J. Eng. Sci. (IJES) 4(11),
1–8 (2015).
[3] Bodhe, V.M., Bhakre, S.M., Ikhar, S.D.: Student attendance system by face detection. Int. J. Innov. Res.
Comput. Commun. Eng. 5(3), 3958 (2017) Author Proof Attendance System with Face Recognition 7.
[4] Chintalapati, S., Raghunadh, M.: Automated attendance management system based on face recognition
algorithms. In: 2013 IEEE International Conference on Computational Intelligence and Computing Research,
pp. 1–5. IEEE (2013).
[5] Deshpande, N.T., Ravishankar, S.: Face detection and recognition using Viola-Jones algorithm and fusion of
PCA and ANN. Adv. Comput. Sci. Technol. 10(5),1173–1189 (2017) .
[6] D’Silva, K., Shanbhag, S., Chaudhari, A., Patil, M.P.: Spot me-a smart attendance system based on face
recognition. Int. Res. J. Eng. Technol. (IRJET) 6(3), 4239 (2019) .
[7] Elias, S.J., Hatim, S.M., Hassan, N.A., Abd Latif, L.M., Ahmad, R.B., Darus, M.Y., Shahuddin, A.Z.: Face
recognition attendance system using local binary pattern (LBP). Bull. Electr. Eng. Inf. 8(1), 239–245 (2019).
[8] Fei-Fei, L., Fergus, R., Perona, P.: One-shot learning of object categories. IEEE Trans. Pattern Anal. Mach.
Intell. 28(4), 594–611 (2006).
[9] Jee, H., Lee, K., Pan, S.: Eye and face detection using SVM. In: Proceedings of the 2004 Intelligent Sensors,
Sensor Networks and Information Processing Conference, 2004, pp. 577–580. IEEE (2004) 10.
[10] Lawrence, S., Giles, C.L., Tsoi, A.C., Back, A.D.: Face recognition: a convolution neural-network approach.
IEEE Trans. Neural Networks 8(1), 98–113 (1997).
[11] M. Sumithra and Dr. S. Malathi, ‖ Modified Global Flower Pollination Algorithm-based image fusion for
medical diagnosis using computed tomography and magnetic resonance imaging‖, International Journal of
Imaging Systems and Technology, Vol. 31, Issue No.1, pp. 223-235, 2021.
[12] B.Buvanswari and T.Kalpalatha Reddy, ―A Review of EEG Based Human Facial Expression Recognition
Systems in Cognitive Sciences‖ International Conference on Enenrgy, Communication,Data analytics and
SoftComputing(ICECDS),CFP17M55-PRJ:978-1-5386-1886-8‖,August 2017.
[13] M. Sumithra and Dr. S. Malathi, ―3D Densealex NET Model with Back Propagation for Brain Tumor
Segmentation‖, International Journal OfCurent Research and Review, Vol. 13, Issue 12, 2021.
[14] K. Sridharan , and Dr. M. Chitra "SBPE: A paradigm Approach for proficient Information Retrieval , Jokull
Journal" , Vol 63, No. 7;Jul 2013
[15] M. Sumithra and Dr. S. Malathi, ―Segmentation Of Different Modalitites Using Fuzzy K-Means And Wavelet
ROI‖, International Journal Of Scientific & Technology Research, Vol. 8, Issue 11, pp. 996-1002, November
2019.
[16] B.Buvaneswari and Dr.T. KalpalathaReddy,―EEG signal classification using soft computing techniques for
brain disease diagnosis‖,Journal of International Pharmaceutical Research ,ISSN : 1674-
0440,Vol.46,No.1,Pp.525-528,2019.
[17] B.Buvaneswari and Dr.T. Kalpalatha Reddy, ―High Performance Hybrid Cognitive Framework for Bio-Facial
Signal Fusion Processing for the Disease Diagnosis‖, Measurement,ISSN: 0263-2241, Vol. 140, Pp.89-99,2019.
[18] K. Sridharan , and Dr. M. Chitra "Web Based Agent And Assertion Passive Grading For Information
Retervial", ARPN Journal of Engineering and Applied Sciences, VOL. 10, NO. 16, September 2015 pp:7043-
7048.
[19] P. Kavitha , R. Subha Shini , R. Priya, "An Implementation Of Statistical Feature Algorithms For The Detection
Of Brain Tumor", Journal of Cognitive Human-Computer Interaction, 2021, DOI:
https://doi.org/10.54216/JCHCI.010202.
[20] Sonia Jenifer Rayen, "Survey On Smart Cane For Visually Impaired Using IOT", Journal of Cognitive Human-
Computer Interaction, 2021, DOI: https://doi.org/10.54216/JCHCI.010205.
[21] Ajith Krishna R , Ankit Kumar , Vijay K, " An Automated Optimize Utilization of Water and Crop Monitoring
in Agriculture Using IoT", Journal of Cognitive Human-Computer Interaction, 2021,
https://doi.org/10.54216/JCHCI.010105.
[22] Ashok Kumar M , Abirami A , Sindhu P , Ashok Kumar V D , Rani V, "Modern Medical Innovation on the
Preferred Information about the Medicine using AI Technique", Journal of Cognitive Human-Computer
Interaction, 2021, https://doi.org/10.54216/JCHCI.010102.
