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Reseach Article

Automated Attendance Management System using Face Recognition

Published on May 2015 by Urvi Jain, Mrunmayee Shirodkar, Varun Sinha, Bhushan Nemade
International Conference and Workshop on Emerging Trends in Technology
Foundation of Computer Science USA
ICWET2015 - Number 2
May 2015
Authors: Urvi Jain, Mrunmayee Shirodkar, Varun Sinha, Bhushan Nemade
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Urvi Jain, Mrunmayee Shirodkar, Varun Sinha, Bhushan Nemade . Automated Attendance Management System using Face Recognition. International Conference and Workshop on Emerging Trends in Technology. ICWET2015, 2 (May 2015), 23-28.

@article{
author = { Urvi Jain, Mrunmayee Shirodkar, Varun Sinha, Bhushan Nemade },
title = { Automated Attendance Management System using Face Recognition },
journal = { International Conference and Workshop on Emerging Trends in Technology },
issue_date = { May 2015 },
volume = { ICWET2015 },
number = { 2 },
month = { May },
year = { 2015 },
issn = 0975-8887,
pages = { 23-28 },
numpages = 6,
url = { /proceedings/icwet2015/number2/20940-5026/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 International Conference and Workshop on Emerging Trends in Technology
%A Urvi Jain
%A Mrunmayee Shirodkar
%A Varun Sinha
%A Bhushan Nemade
%T Automated Attendance Management System using Face Recognition
%J International Conference and Workshop on Emerging Trends in Technology
%@ 0975-8887
%V ICWET2015
%N 2
%P 23-28
%D 2015
%I International Journal of Computer Applications
Abstract

Face Detection and Recognition is an important area in the field of substantiation. Maintenance of records of students along with monitoring of class attendance is an area of administration that requires significant amount of time and efforts for management. Automated Attendance Management System performs the daily activities of attendance analysis, for which face recognition is an important aspect. The prevalent techniques and methodologies for detecting and recognizing face like PCA-LDA, etc fail to overcome issues such as scaling, pose, illumination, variations, rotation, and occlusions. The proposed system provides features such as detection of faces, extraction of the features, detection of extracted features, analysis of students' attendance and monthly attendance report generation. The proposed system integrates techniques such as image contrasts, integral images, Ada-Boost, Haar-like features and cascading classifier for feature detection. Faces are recognized using advanced LBP using the database that contains images of students and is used to recognize student using the captured image. Better accuracy is attained in results and the system takes into account the changes that occurs in the face over the period of time.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Pca-lda Ada-boost Cascading Classifier Background Regions.