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논문검색

Hybrid Face Recognition using Image Feature Extractions : A Review

초록

영어

Face recognition is an image processing technique that recognizes the face of a person in the system. Face recognizing system may comprise the circuit board, software for detecting face with programmatic assurance. Face recognition developed in neural networks is the major application development in present days. This process can be used in security and biometric applications. For providing more security considerations proposed technique was Hybrid Face Recognition with Radial Basis Function, that uses two algorithms like PCA and LDA for face feature extraction and dimensionally fusion methods for associated to PCA and LDA. We will plan to extend our existing approach for feature extraction with different stages. In this we propose four stages for recognizing image extraction in facial schema. In this process the recognized image is determined by the corresponding output value present within threshold description. Our experimental shows efficient security considerations on facial feature extraction process.

목차

Abstract
 1. Introduction
 2. Neural Networks
 3. Background Work
 4. Our Work
  4.1. Face Preprocessing (or) Normalization
  4.2. Feature Extraction using PCA & LDA
  4.3. Feature Fusion using PCA
  4.4. Classification using RBF
 5. Conclusion
 References

저자정보

  • Venkata Naresh Mandhala Vignan’s Foundation for Science, Technology and Research University, Vadlamudi, Guntur, AP, India
  • Debnath Bhattacharyya Department of Computer Application, RCC Institute of Information Technology, Canal South Road, Beliaghata, Kolkata - 700015, India
  • Tai-hoon Kim Department of Convergence Security, Sungshin Women's University, 249-1, Dongseon-dong 3-ga, Seoul, 136-742, Korea

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