Automated Student Attendance Using Facial Recognition Based On DRLBP &DRLDP

The project presents an automated attendance system based on face recognition using discriminative robust local binary pattern and local directional pattern descriptors.The proposed system involves face detection,features extraction and matching.The face detection is used to detect faces based on Vi...

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Bibliographic Details
Published in:International journal of advanced networking and applications 2019-01, p.193-196
Main Authors: Deepika, G, Agarwal, M Priya, Aarthi, K C
Format: Article
Language:English
Subjects:
Algorithms
Automation
Digitization
Face recognition
Facial recognition technology
Feature extraction
Image contrast
Integrated software
Robustness
Smartphones
Social networks
Time and attendance systems
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Summary:The project presents an automated attendance system based on face recognition using discriminative robust local binary pattern and local directional pattern descriptors.The proposed system involves face detection,features extraction and matching.The face detection is used to detect faces based on Viola Jones algorithm using vision toolbox.In feature extraction stage,the discriminative robust local binary pattern is used for different object texture and edge contour feature extraction process.A DRLDP operator computes the edge response values in all eight directions at each pixel position and generates a code from the relative strength magnitude.The proposed features retain The contrast information of image patterns.These features are useful to distinguish he maximum number of samples accurately and it is matched with already stored image samples for person verification.The simulated results will be shown that used methodologies have better discriminatory power and recognition accuracy compared with prior approaches.
ISSN:0975-0290
0975-0282