Journal of Digital Contents Society (디지털콘텐츠학회 논문지)

Digital Contents Society (한국디지털콘텐츠학회)
권호 표지
DOI QR코드

DOI QR Code

Face Detection in Near Infra-red for Human Recognition

휴먼 인지를 위한 근적외선 영상에서의 얼굴 검출

  • 이경숙 (경북대학교 IT대학 모바일통신공학과) ;
  • 김현덕 (경북대학교 IT대학)
  • Received : 2012.03.14
  • Accepted : 2012.06.11
  • Published : 2012.06.30
Download PDF
⟨ Previous Next ⟩

Abstract

In this paper, face detection method in NIR(Near-InfraRed) images for human recognition is proposed. Edge histogram based on edge intensity and its direction, has been used to detect effectively faces on NIR image. The edge histogram descripts and discriminates face effectively because it is strong in environment of lighting change. SVM(Support Vector Machine) has been used as a classifier to detect face and the proposed method showed better performance with smaller features than in ULBP(Uniform Local Binary Pattern) based method.

본 논문에서는 휴먼 인지를 위한, 근적외선 얼굴 영상에서의 얼굴 검출 방법이 제안된다. 에지의 강도와 방향에 기반한 에지 히스토그램이 근적외선 영상으로부터 얼굴을 검출하기 위해 사용되었다. 조명변화에 강인하기 때문에, 제안된 에지 히스토그램은 얼굴을 효과적으로 표현하고 구별한다. 얼굴 검출을 위한 분류기로서는 SVM(Support Vector Machine)을 사용하였으며 제안한 방법은 ULBP(Uniform Local Binary Pattern)보다 적은 피쳐 개수를 가지면서도 에러율 측면에서, ULBP의 경우보다 나은 성능을 나타내었다.

Keywords

References

  1. S. Gundimada and V. Asari, "Face detection technique based on rotation invariant wavelet features," Int'sConf.,InformationTechnology: Coding and Computing,vol.2,pp.157-158,Apr.2004.
  2. F. Y. Shih and C. F. Chuang, "Automatic extraction of head and face boundaries and facial feature," Information Sciences,vol.158,pp.117-130,Jan.2004. https://doi.org/10.1016/j.ins.2003.03.002
  3. Y. J. Fen. and P. F. Shi, "Face detection based on kernel fisher discriminant analysis," Proc.sixthIEEE Int'lConf., Automatic Faceand Gesture Recognition, pp.381-384,May.2004.
  4. A. Tolba, A. El-Baz, and A. El-Harby, "Face Recogn ition: A Literature Review," Intern. Journ. of Signal Processing,Vol.2,No.2,pp.88-103,2006.
  5. W. Zhao, "Face Recognition: A Literature Survey," ACM Computing Surveys,Vol.35,No.4,pp.339-458,2003.
  6. S. Xie, S. Shan, X. Chen, and J. Chen "Fusing Local Patterns of Gabor Magnitude and Ph ase for Face Recognition," IEEE Trans. on Image Processing,Vol.19,No.5,pp.1349-1361,May2010. https://doi.org/10.1109/TIP.2010.2041397
  7. T. Ojala, M. Pietikainen and T. Maenpaa, "Multiresolution gray-scale and rotation invariant texture classification with local binary patterns", IEEE Transactionon Pattern Analysis and Machine intelligence,vol.24,pp.971-987,2002. https://doi.org/10.1109/TPAMI.2002.1017623
  8. C. Shan, S. Gong and P. W. McOwan, "Facial expression recognition based on local binary pattern: A comprehensive study", Image and Vision Computing,v ol.27,pp.803-816,2009. https://doi.org/10.1016/j.imavis.2008.08.005
  9. T. Ahonen, A. Hadid, and M. Pietikainen, "Face recognition with local binary patterns," ECCV,pp.469-481,2004.
  10. G. Zhang, X. Huang, S. Z. Li, Y. Wang, and X. Wu, "Boosting local binary pattern based face recognition", Proc. Advances in Biometric Person Authentication,vol.3338,pp.179-186,2004.
  11. T. Ahonen, A. Hadid, and M. Pietikäinen, "Face description with Local Binary Patterns: Application to Face Recognition", IEEE Trans. Pattern Analysis a nd Machine Intelligence, vol. 28, no. 12, Dec. 2006, pp.2037-2041. https://doi.org/10.1109/TPAMI.2006.244
  12. T. Ahonen and M. Pietikainen, "Soft histograms for local binary patterns", Proc. Finnish Signal Processing Symposium (FINSIG 2007),Oulu,Finland,2007.
  13. Y. Li, S. Gong, J. Sharrah and H. Liddell, " Support vector machine based multi-view face detection and recognition", ImageandVisioncomputing,vol.22,pp.413-127,2004. https://doi.org/10.1016/j.imavis.2003.12.005
  14. Y. J. Feng and P. F. Shi, "Face detection based on Kernel Fisher Discriminant analysis", Proc.sixthIEEEInt'lconf., Automatic Face and Gesture Recognition,pp.381-384,May.2004.
  15. C. A. Waring and X. Liu, "Face Detection Using Spectral Histograms and SVMs", IEEE Trans. Systems, Manand Cybernetics,vol.99,pp.467-476,Apr.2005.