Table of Contents Author Guidelines Submit a Manuscript
The Scientific World Journal
Volume 2014 (2014), Article ID 628494, 15 pages
http://dx.doi.org/10.1155/2014/628494
Research Article

Color Face Recognition Based on Steerable Pyramid Transform and Extreme Learning Machines

Mechatronics Engineering Department, Engineering Faculty, Firat University, 23119 Elazig, Turkey

Received 12 August 2013; Accepted 7 October 2013; Published 16 January 2014

Academic Editors: S. Bourennane and J. Marot

Copyright © 2014 Ayşegül Uçar. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. X. Jing, S. Li, C. Lan, D. Zhang, J. Yang, and Q. Liu, “Color image canonical correlation analysis for face feature extraction and recognition,” Signal Processing, vol. 91, no. 8, pp. 2132–2140, 2011. View at Publisher · View at Google Scholar · View at Scopus
  2. J. Y. Choi, Y. M. Ro, and K. N. Plataniotis, “Color face recognition for degraded face images,” IEEE Transactions on Systems, Man, and Cybernetics, Part B, vol. 39, no. 5, pp. 1217–1230, 2009. View at Publisher · View at Google Scholar · View at Scopus
  3. R.-L. Hsu, M. Abdel-Mottaleb, and A. K. Jain, “Face detection in color images,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 24, no. 5, pp. 696–706, 2002. View at Publisher · View at Google Scholar · View at Scopus
  4. M. Villegas, R. Paredes, A. Juan, and E. Vidal, “Face verification on color images using local features,” in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPRW ’08), pp. 1–6, Anchorage, Alaska, USA, June, 2008. View at Publisher · View at Google Scholar
  5. J. Yang, C. Liu, and L. Zhang, “Color space normalization: enhancing the discriminating power of color spaces for face recognition,” Pattern Recognition, vol. 43, no. 4, pp. 1454–1466, 2010. View at Publisher · View at Google Scholar · View at Scopus
  6. S. Yoo, D. G. Sim, Y. G. Kim, and R. H. Park, “Performance comparison of principal component analysis-based face recognition in color space,” in Advanced Biometric Technologies, G. Chetty and J. Yang, Eds., pp. 281–296, InTech, Rijeka, Croatia, 2011. View at Google Scholar
  7. J. Yang, C. Liu, and J.-Y. Yang, “What kind of color spaces is suitable for color face recognition?” Neurocomputing, vol. 73, no. 10-12, pp. 2140–2146, 2010. View at Publisher · View at Google Scholar · View at Scopus
  8. Z. Liu and C. Liu, “A hybrid color and frequency features method for face recognition,” IEEE Transactions on Image Processing, vol. 17, no. 10, pp. 1975–1980, 2008. View at Publisher · View at Google Scholar · View at Scopus
  9. Z. Liu and C. Liu, “Fusion of color, local spatial and global frequency information for face recognition,” Pattern Recognition, vol. 43, no. 8, pp. 2882–2890, 2010. View at Publisher · View at Google Scholar · View at Scopus
  10. C. Liu, “Extracting discriminative color features for face recognition,” Pattern Recognition Letters, vol. 32, no. 14, pp. 1796–1804, 2011. View at Publisher · View at Google Scholar · View at Scopus
  11. J. Y. Choi, Y. M. Ro, and K. N. Plataniotis, “Color local texture features for color face recognition,” IEEE Transactions on Image Processing, vol. 21, no. 3, pp. 1366–1380, 2012. View at Publisher · View at Google Scholar · View at Scopus
  12. E. P. Simoncelli, W. T. Freeman, E. H. Adelson, and D. J. Heeger, “Shiftable multiscale transforms,” IEEE Transactions on Information Theory, vol. 38, no. 2, pp. 587–607, 1992. View at Publisher · View at Google Scholar · View at Scopus
  13. M. El Aroussi, M. El Hassouni, S. Ghouzali, M. Rziza, and D. Aboutajdine, “Local appearance based face recognition method using block based steerable pyramid transform,” Signal Processing, vol. 91, no. 1, pp. 38–50, 2011. View at Publisher · View at Google Scholar · View at Scopus
  14. G.-B. Huang, Q.-Y. Zhu, and C.-K. Siew, “Real-time learning capability of neural networks,” IEEE Transactions on Neural Networks, vol. 17, no. 4, pp. 863–878, 2006. View at Publisher · View at Google Scholar · View at Scopus
  15. G.-B. Huang, Q.-Y. Zhu, and C.-K. Siew, “Extreme learning machine: theory and applications,” Neurocomputing, vol. 70, no. 1–3, pp. 489–501, 2006. View at Publisher · View at Google Scholar · View at Scopus
  16. G.-B. Huang, L. Chen, and C.-K. Siew, “Universal approximation using incremental constructive feedforward networks with random hidden nodes,” IEEE Transactions on Neural Networks, vol. 17, no. 4, pp. 879–892, 2006. View at Publisher · View at Google Scholar · View at Scopus
  17. G.-B. Huang and L. Chen, “Convex incremental extreme learning machine,” Neurocomputing, vol. 70, no. 16-18, pp. 3056–3062, 2007. View at Publisher · View at Google Scholar · View at Scopus
  18. G.-B. Huang, H. Zhou, X. Ding, and R. Zhang, “Extreme learning machine for regression and multiclass classification,” IEEE Transactions on Systems, Man, and Cybernetics, Part B, vol. 42, no. 2, pp. 513–529, 2012. View at Publisher · View at Google Scholar · View at Scopus
  19. K. Choi, K.-A. Toh, and H. Byun, “Incremental face recognition for large-scale social network services,” Pattern Recognition, vol. 45, no. 8, pp. 2868–2883, 2012. View at Publisher · View at Google Scholar · View at Scopus
  20. A. A. Mohammed, R. Minhas, Q. M. Jonathan Wu, and M. A. Sid-Ahmed, “Human face recognition based on multidimensional PCA and extreme learning machine,” Pattern Recognition, vol. 44, no. 10-11, pp. 2588–2597, 2011. View at Publisher · View at Google Scholar · View at Scopus
  21. P. J. Phillips, H. Moon, S. A. Rizvi, and P. J. Rauss, “The FERET evaluation methodology for face-recognition algorithms,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 22, no. 10, pp. 1090–1104, 2000. View at Publisher · View at Google Scholar · View at Scopus
  22. A. Martinez and R. Benavente, “The AR face database,” CVC Technical Report 24, Universitat Autònoma de Barcelona, Barcelona, Spain, 1998. View at Google Scholar
  23. A. Uçar, “Facial expression recognition based on significant face components using steerable pyramid transform,” in Proceedings of the International Conference on Image Processing, Computer Vision and Pattern Recognition (IPCV ’13), vol. 2, pp. 687–692, Las Vegas, Nev, USA, July, 2013.
  24. V. Vapnik, The Nature of Statistical Learning Theory, Springer, New York, Ny, USA, 1st edition, 1995.
  25. K. Jack, Video Demystified: A Handbook for the Digital Engineer, LLH Technology Publishing, Eagle Rock, Va, USA, 3rd edition, 2001.
  26. J. M. Chaves-González, M. A. Vega-Rodríguez, J. A. Gómez-Pulido, and J. M. Sánchez-Pérez, “Detecting skin in face recognition systems: a colour spaces study,” Digital Signal Processing, vol. 20, no. 3, pp. 806–823, 2010. View at Publisher · View at Google Scholar
  27. S. V. Tathe and S. P. Narote, “Face detection using color models,” World Journal of Science and Technology, vol. 2, no. 4, pp. 182–185, 2012. View at Google Scholar
  28. C. Garcia, G. Zikos, and G. Tziritas, “Face detection in color images using wavelet packet analysis,” in Proceedings of the IEEE Multimedia Computing and Systems (ICMCS ’99), vol. I, pp. 703–708, Florence, Italy, June, 1999. View at Publisher · View at Google Scholar
  29. D. Chai and K. N. Ngan, “Face segmentation using skin-color map in videophone applications,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 9, no. 4, pp. 551–564, 1999. View at Publisher · View at Google Scholar · View at Scopus
  30. K.-W. Wong, K.-M. Lam, and W.-C. Siu, “A robust scheme for live detection of human faces in color images,” Signal Processing: Image Communication, vol. 18, no. 2, pp. 103–114, 2003. View at Publisher · View at Google Scholar · View at Scopus
  31. S. M. Lajevardi and H. R. Wu, “Facial expression recognition in perceptual color space,” IEEE Transactions on Image Processing, vol. 21, no. 8, pp. 3721–3733, 2012. View at Publisher · View at Google Scholar
  32. P. Shih and C. Liu, “Comparative assessment of content-based face image retrieval in different color spaces,” International Journal of Pattern Recognition and Artificial Intelligence, vol. 19, no. 7, pp. 873–893, 2005. View at Publisher · View at Google Scholar · View at Scopus
  33. A. Uçar, “Color face recognition based on curvelet transform,” in Proceedings of the International Conference on Image Processing, Computer Vision and Pattern Recognition (IPCV ’12), vol. 2, pp. 561–566, Las Vegas, Nev, USA, July, 2012.
  34. J. Kittler, M. Hatef, R. P. W. Duin, and J. Matas, “On combining classifiers,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 20, no. 3, pp. 226–239, 1998. View at Publisher · View at Google Scholar · View at Scopus
  35. A. M. Martinez and A. C. Kak, “PCA versus LDA,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 23, no. 2, pp. 228–233, 2001. View at Publisher · View at Google Scholar · View at Scopus
  36. C. W. Hsu, C. C. Chang, and C. J. Lin, “A practical guide to support vector classification,” Tech. Rep., National Taiwan University, Department of Computer Science, Taipei, Taiwan, 2003, http://www.csie.ntu.edu.tw/~cjlin/papers/guide/guide.pdf. View at Google Scholar
  37. A. Uçar, Y. Demir, and C. Güzeliş, “A Penalty function method for designing efficient robust classifiers with input-space optimal separating surfaces,” Turkish Journal of Electrical Engineering and Compute Sciences. In press. View at Publisher · View at Google Scholar
  38. A. P. James and S. Dimitrijev, “Face recognition using local binary decisions,” IEEE Signal Processing Letters, vol. 15, pp. 821–824, 2008. View at Publisher · View at Google Scholar · View at Scopus
  39. S. H. Lee, J. Y. Choi, Y. M. Ro, and K. N. Plataniotis, “Local color vector binary patterns from multichannel face images for face recognition,” IEEE Transactions on Image Processing, vol. 21, no. 4, pp. 2347–2353, 2012. View at Publisher · View at Google Scholar · View at Scopus