Earticle

초록

영어

Facial part detection or extraction shows the most important role in face and eye recognition. In this article proposed a new algorithm for Face and Eye Recognition (FER) using radial basis function support vector machine (RBFSVM) classifier. The discrete wavelet transform (DWT) is used for feature extraction and selection. For the experimental results, used JAFFE and ORL database. In this algorithm, extract face component like left eye, right eye, mouth and nose. In the preprocessing stage, apply median filtering for removing noise from an image. This stage improves the feature extraction process. Finding an image from the image components is a typical task in pattern recognition. The detection rate has reached up to100% for eye recognition and for face recognition is 90-96%. The proposed system estimates the value of precision and recall. This algorithm is compared with SVM and our proposed proved better than previous algorithms.

목차

Abstract
 1. Introduction
 2. Related Work
 3. Proposed Methodology
 4. Proposed Algorithm
 5. Image Dataset
 6. Performance Evaluation
 7. Conclusion
 References

키워드

저자

• Naveen Kumar Ahirwar [ Department of Computer Science Engineering and Information Technology Madhav Institute of Technology & Science, Gwalior, India ]
• Manish Dixit [ Department of Computer Science Engineering and Information Technology Madhav Institute of Technology & Science, Gwalior, India ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Signal Processing, Image Processing and Pattern Recognition

• 간기

  격월간

• pISSN

  2005-4254

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605