원문정보
보안공학연구지원센터(IJSIA)
International Journal of Security and Its Applications
Vol.8 No.5
2014.09
pp.253-264
피인용수 : 0건 (자료제공 : 네이버학술정보)
초록
영어
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
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
저자정보
참고문헌
자료제공 : 네이버학술정보