TY - GEN
T1 - An approach to maintain attendance using image processing techniques
AU - Yuvaraj, C. B.
AU - Srikanth, M.
AU - Santhosh Kumar, V.
AU - Srinivasa Murthy, Y. V.
AU - Koolagudi, Shashidhar G.
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/7/2
Y1 - 2017/7/2
N2 - Nowadays, the research is growing towards the invention of new approaches. One such most attracted application is face recognition of image processing. There are several innovative technologies have been developed to take attendance. Some prominent ones are biometric, thumb impressions, access card, and fingerprints. The method proposed in this paper is to record the attendance through image using face detection and face recognition. The proposed approach has been implemented in four steps such as face detection, labelling the detected faces, training a classifier based on labelled dataset, and face recognition. The database has been constructed with the positive images and negative images. The complete database has been divided into training and testing set and further, processed by a classifier to recognize the faces in a classroom. The final step is to take the attendance using face recognition technique in which the input image of a classroom is given, and faces of the given image will be detected along with their IDs. The frames of a video taken for a minute is taken into consideration to avoid the missed ones due to rotational issues.
AB - Nowadays, the research is growing towards the invention of new approaches. One such most attracted application is face recognition of image processing. There are several innovative technologies have been developed to take attendance. Some prominent ones are biometric, thumb impressions, access card, and fingerprints. The method proposed in this paper is to record the attendance through image using face detection and face recognition. The proposed approach has been implemented in four steps such as face detection, labelling the detected faces, training a classifier based on labelled dataset, and face recognition. The database has been constructed with the positive images and negative images. The complete database has been divided into training and testing set and further, processed by a classifier to recognize the faces in a classroom. The final step is to take the attendance using face recognition technique in which the input image of a classroom is given, and faces of the given image will be detected along with their IDs. The frames of a video taken for a minute is taken into consideration to avoid the missed ones due to rotational issues.
UR - https://www.scopus.com/pages/publications/85046365967
UR - https://www.scopus.com/pages/publications/85046365967#tab=citedBy
U2 - 10.1109/IC3.2017.8284353
DO - 10.1109/IC3.2017.8284353
M3 - Conference contribution
AN - SCOPUS:85046365967
T3 - 2017 10th International Conference on Contemporary Computing, IC3 2017
SP - 1
EP - 3
BT - 2017 10th International Conference on Contemporary Computing, IC3 2017
A2 - Alum, Srinivas
A2 - Kalyanararnan, Ananth
A2 - Ucar, Bora
A2 - Kothapalli, Kishor
A2 - Halappanavar, Mahantesh
A2 - Madduri, Kamesh
A2 - Govindaraju, Madhu
A2 - Xia, Yinglong
A2 - Prasad, Sushil
A2 - Barnas, Martina
A2 - Sureka, Ashish
A2 - Patel, Pankesh
A2 - Saxena, Vikas
A2 - Goel, Sanjay
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 10th International Conference on Contemporary Computing, IC3 2017
Y2 - 10 August 2017 through 12 August 2017
ER -