Indian Journal of Science and Technology
Year: 2020, Volume: 13, Issue: 13, Pages: 1401-1411
Kamlesh Kumar1, Asif Ali Wagan1*, Mansoor Ahmed Khuhro1, Aamir Umrani1, Ameen Chhajro1, Abdul Hafeez1, Asif Ali Laghari1
1Department of Computer Science, Sindh Madressatul Islam University, Karachi
Asif Ali Wagan
Department of Computer Science, Sindh Madressatul Islam University, Karachi
Email: [email protected]
Received Date:03 April 2020, Accepted Date:23 April 2020, Published Date:22 May 2020
Objectives: Automatic face recognition has been an important area of biometric authentication and verification system in various applications including crime detection, access control, video surveillance, tracking service and other related areas. Methods/Statistical analysis: In this study, we present Grey Level Co-occurrence Matrix (GLCM) over Local Binary Patterns (LBP) named as GOL texture feature technique for face classification. The experiments have been conducted on AT & T Cambridge Laboratory face images also called (ORL-faces) and Georgia Tech (GT-faces) databases respectively. Findings: We performed a comparative analysis of GLCM and LBP method separately and results showed that the proposed GOL method outperformed in terms of average sensitivity, average specificity, and retrieval time. These findings show efficacy of our proposed system.
Keywords: GLCM; LBP; Face recognition; Feature extraction
Copyright: © 2020 Kumar, Wagan, Khuhro, Umrani, Chhajro, Hafeez, Laghari. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Published By Indian Society for Education and Environment (iSee)
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