IEEE Style Citation: Anjana Pandey, Kanika Gupta, Shivang Agrawal, “Automatic Attendance Recording Using Face Recognition,” International Journal of Computer Sciences and Engineering, Vol.7, Issue.6, pp.266-275, 2019.
MLA Style Citation: Anjana Pandey, Kanika Gupta, Shivang Agrawal "Automatic Attendance Recording Using Face Recognition." International Journal of Computer Sciences and Engineering 7.6 (2019): 266-275.
APA Style Citation: Anjana Pandey, Kanika Gupta, Shivang Agrawal, (2019). Automatic Attendance Recording Using Face Recognition. International Journal of Computer Sciences and Engineering, 7(6), 266-275.
BibTex Style Citation:
@article{Pandey_2019,
author = {Anjana Pandey, Kanika Gupta, Shivang Agrawal},
title = {Automatic Attendance Recording Using Face Recognition},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {6 2019},
volume = {7},
Issue = {6},
month = {6},
year = {2019},
issn = {2347-2693},
pages = {266-275},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=4541},
doi = {https://doi.org/10.26438/ijcse/v7i6.266275}
publisher = {IJCSE, Indore, INDIA},
}
RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i6.266275}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=4541
TI - Automatic Attendance Recording Using Face Recognition
T2 - International Journal of Computer Sciences and Engineering
AU - Anjana Pandey, Kanika Gupta, Shivang Agrawal
PY - 2019
DA - 2019/06/30
PB - IJCSE, Indore, INDIA
SP - 266-275
IS - 6
VL - 7
SN - 2347-2693
ER -
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Abstract
Face Recognition is an application in the computer vision industry .Many algorithms has been developed in order to achieve facial recognition with most accuracy. Face recognition is less sturdy than other biometric scanning systems like fingerprint and retina scanning. This report describes the face detection and recognition minor-project developed for the attendance system of the department where a student can view his attendance on the dates present and teacher can check the attendance and save it in pdf format. This project uses the technologies available in the OpenComputerVision (OpenCV) library in java interface and methods to implement them using . This project is accomplished using Haar-Cascades for face detection and Local binary pattern histograms(LBPH) for face recognition. The process is represented together with flow charts for every stage of the system. Next, the results are shown using screen-shots.
Key-Words / Index Term
Facial Recognition, Local Binary Patterns Histograms, Facial detection, Haar features, Computer Vision, OpenCV
References
[1] Ayushi gupta, Ekta Sharma, Neha sachan and neha Tiwari, “Door Lock System through Face Recognition Using MATLAB”, IJSRCSE (International Journal of Scientific Research in Computer Science andEngineering), 2013
[2] Face Recognition Based on HOG and Fast PCA Algorithm Xiang-Yu Li(&) and Zhen-Xian Li
[3] Dinalankara, Lahiru. (2017). Face Detection & Face Recognition Using Open Computer Vision Classifies.
[4] Study of Various Face Detection Methods , Ms.Varsha Gupta1 , Mr. Dipesh Sharma2,ijarcce vol.3
[5] Prabhjot Singh1 and Anjana Sharma “Face Recognition Using Principal Component Analysis in MATLAB” ”, IJSRCSE (International Journal of Scientific Research in Computer Science andEngineering), vol 3,issue 1 2014
[6]. Kelvin Salton do Prado “Face Recognition: Understanding LBPH Algorithm” towardsdatascience.com
[7] Nicolas Delbiaggio “A comparison of facial recognition’s algorithms “ Hagga-Helia university of applied science
[8] Ahonen, Timo, Abdenour Hadid, and Matti Pietikäinen. “Face recognition with local binary patterns.” Computer vision-eccv 2004 (2004): 469–481.
[9] Matti Pietikäinen (2010) Local Binary Patterns. Scholarpedia, 5(3):9775
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