As for illumination variation, traditional feature extraction methods are not satisfactory for face recognition. A block discriminant analysis algorithm is proposed to solve the problem. Firstly, local contrast enhancement is used to compensate for uneven illumination; secondly, discrete cosine transform (DCT) is implemented for divided image blocks. According to data distribution of DCT matrix, the block candidate features are selected, and merged to candidate features; finally, block discriminant analysis are carried out for features extraction. Experiments are tested on Yale and Yale B, the results prove the algorithm outperform related algorithms.
목차
Abstract 1. Introduction 2. Local Contrast Enhancement for Preprocessing Images 3. Block Discriminant Analysis for Feature Extraction 3.1. Block DCT Transform 3.2 Calculation for Block Discriminant Factor 3.3. LCE+BDA Algorithm 4. Experiment and Result Analysis 4.1. Experiment Result 4.2 Evaluation on Performance 5. Conclusion and Future Work Acknowledgements References
키워드
Face recognitionFeature extractionDiscrete cosine transformDiscriminant analysis
저자
Peng Cui [ School of Computer Science & technology, Harbin University of Science and Technology, Harbin, China ]
보안공학연구지원센터(IJSIA) [Science & Engineering Research Support Center, Republic of Korea(IJSIA)]
설립연도
2006
분야
공학>컴퓨터학
소개
1. 보안공학에 대한 각종 조사 및 연구
2. 보안공학에 대한 응용기술 연구 및 발표
3. 보안공학에 관한 각종 학술 발표회 및 전시회 개최
4. 보안공학 기술의 상호 협조 및 정보교환
5. 보안공학에 관한 표준화 사업 및 규격의 제정
6. 보안공학에 관한 산학연 협동의 증진
7. 국제적 학술 교류 및 기술 협력
8. 보안공학에 관한 논문지 발간
9. 기타 본 회 목적 달성에 필요한 사업
간행물
간행물명
International Journal of Security and Its Applications
간기
격월간
pISSN
1738-9976
수록기간
2008~2016
등재여부
SCOPUS
십진분류
KDC 505DDC 605
이 권호 내 다른 논문 / International Journal of Security and Its Applications Vol.8 No.5