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RISS 인기검색어
- 검색키워드
- 저자 : G. Madasamy Raja (검색결과 2 건)
- 무료
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- 유료
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Face Representation and Face Recognition using Optimized Local Ternary Patterns (OLTP)
G. Madasamy Raja,V. Sadasivam 대한전기학회 2017 Journal of Electrical Engineering & Technology Vol.12 No.1
For many years, researchers in face description area have been representing and recognizing faces based on different methods that include subspace discriminant analysis, statistical learning and non-statistics based approach etc. But still automatic face recognition remains an interesting but challenging problem. This paper presents a novel and efficient face image representation method based on Optimized Local Ternary Pattern (OLTP) texture features. The face image is divided into several regions from which the OLTP texture feature distributions are extracted and concatenated into a feature vector that can act as face descriptor. The recognition is performed using nearest neighbor classification method with Chi-square distance as a similarity measure. Extensive experimental results on Yale B, ORL and AR face databases show that OLTP consistently performs much better than other well recognized texture models for face recognition.
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Face Representation and Face Recognition using Optimized Local Ternary Patterns (OLTP)
Raja, G. Madasamy,Sadasivam, V. The Korean Institute of Electrical Engineers 2017 Journal of Electrical Engineering & Technology Vol.12 No.1
For many years, researchers in face description area have been representing and recognizing faces based on different methods that include subspace discriminant analysis, statistical learning and non-statistics based approach etc. But still automatic face recognition remains an interesting but challenging problem. This paper presents a novel and efficient face image representation method based on Optimized Local Ternary Pattern (OLTP) texture features. The face image is divided into several regions from which the OLTP texture feature distributions are extracted and concatenated into a feature vector that can act as face descriptor. The recognition is performed using nearest neighbor classification method with Chi-square distance as a similarity measure. Extensive experimental results on Yale B, ORL and AR face databases show that OLTP consistently performs much better than other well recognized texture models for face recognition.
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