Earticle

초록

영어

In this paper we describe our implementation of algorithms for face detection and recognition in color images under Matlab. For face detection, we trained a feedforward neural network to perform skin segmentation, followed by the eyes detection, face alignment, lips detection and face delimitation. The eyes were detected by analyzing the chrominance and the angle between neighboring pixels and, then, the results were used to perform face alignment. The lips were detected based on the analysis of the Red color component intensity in the lower face region. Finally, the faces were delimited using the eyes and lips positions. The face recognition involved a classifier that used the standard deviation of the difference between color matrices of the faces to identify the input face. The algorithms were run on Faces 1999 dataset. The proposed method achieved 96.9%, 89% and 94% correct detection rate of face, eyes and lips, respectively. The correctness rate of the face recognition algorithm was 70.7%.

목차

Abstract
 1. Introduction
 2. Color Spaces
 3. Image Processing and Neural Networks in Matlab
 4. Face Detection
  4.1. Face Localization
  4.2. Eyes Detection
  4.3. Face Alignment
  4.4. Lips Detection
  4.5. Faces Delimitation
  4.6. Resizing and Brightness-Leveling
 5. Faces Recognition/Classification
 6. Experimental Results and Discussion
 7. Conclusion
 8. Future Works
 References

키워드

저자

• Deise Maia [ Depatment of Computer Science, Federal University of Minas Gerais, Belo Horizonte, Brazil ]
• Roque Trindade [ Department of Mathematical Sciences, State University of Southwest Bahia, Vitória da Conquista, Brazil ]

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