No abstract

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 area. 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 comparative analysis of GLCM and LBP method separately and results showed that proposed GOL method outperformed in terms of average sensitivity, average specificity, and retrieval time. These findings show efficacy of our proposed system.