A Two-Part Approach to Face Recognition: Generalized Hough Transform and Image Descriptors

Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 318)


This research considers a two-part approach to the problem of face recognition. The first part, based on a variant of the generalized Hough transform, takes a global view of the matter, specifically the edges that make up a sketch of a face. The second component, on the other hand, examines the local features of a given face using a novel image descriptor, known as the gradient distance descriptor. The proposed technique performs well in testing. Moreover, this method does not require any training and may be extended to general object recognition.


Face recognition Generalized Hough transform Image descriptors. 


  1. 1.
    Li, S., Jain, A. (eds.): Handbook of Face Recognition, 2nd edn. Springer, New York (2011)MATHGoogle Scholar
  2. 2.
    Liu, L., Özsu, M. (eds.): Encyclopedia of Database Systems. Springer, New York (2009)MATHGoogle Scholar
  3. 3.
    Ballard, D.: Generalizing the Hough transform to detect arbitrary shapes. Pattern Recognit. 13, 111–122 (1981)CrossRefMATHGoogle Scholar
  4. 4.
    Goshtasby, A.: Image Registration: Principles, Tools and Methods. Springer, New York (2012)CrossRefGoogle Scholar
  5. 5.
    Yale Face Database. Retrieved July 4, 2012 from (1997)
  6. 6.
    Moise, M., Yang, X. D., Dosselmann, R.: Face recognition using modified generalized Hough transform and gradient distance descriptor. In: Proceedings of the 2nd International Conference Pattern Recognition Applications and Methods (2013)Google Scholar
  7. 7.
    Moise, M.: A new approach to face recognition based on generalized Hough transform and local image descriptors. Master’s thesis. University of Regina, Regina, Canada (2012)Google Scholar
  8. 8.
    Li, M.-J., Dai, R.-W.: A personal handwritten Chinese character recognition algorithm based on the generalized Hough transform. In: Proceedings of the International Conference Document Analysis and Recognition, vol. 2, pp. 828–831 (1995)Google Scholar
  9. 9.
    Li, Q., Zhang, B.: Image matching under generalized Hough transform. In: Proceedings of the IADIS International Conference Applied Computing, pp. 45–50 (2005)Google Scholar
  10. 10.
    Anelli, M., Cinque, L., Sangineto, E.: Deformation tolerant generalized Hough transform for sketch-based image retrieval in complex scenes. Image Vis. Comput. 25, 1802–1813 (2007)CrossRefGoogle Scholar
  11. 11.
    Schubert, A.: Detection and tracking of facial features in real time using a synergistic approach of spatio-temporal models and generalized Hough transform techniques. In: Proceedings of the 4th IEEE International Conference Automatic Face and Gesture Recognition, pp. 116–121 (2000)Google Scholar
  12. 12.
    Gall, J., Lempitsky, V.: Class-specific Hough forests for object detection. In: Proceedings of the IEEE Conference Computer Vision and Pattern Recognition (2009)Google Scholar
  13. 13.
    Barinova, O., Lempitsky, V., Kohli, P.: On detection of multiple object instances using Hough transforms. In: Proceedings of the IEEE Conference Computer Vision and Pattern Recognition, pp. 2233–2240 (2010)Google Scholar
  14. 14.
    Turk, M., Pentland, A.: Eigenfaces for recognition. J. Cognit. Neurosci. 3, 71–86 (1991)CrossRefGoogle Scholar
  15. 15.
    Belhumeur, P., Hespanha, J., Kriegman, D.: Eigenfaces versus fisherfaces: recognition using class specific linear projection. IEEE Trans. Pattern Anal. Mach. Intell. 19, 711–720 (1997)CrossRefGoogle Scholar
  16. 16.
    Zhao, W., Chellappa, R., Phillips, P.J., Rosenfeld, A.: Face recognition: a literature survey. ACM Comput. Surv. 35, 399–458 (2003)CrossRefGoogle Scholar
  17. 17.
    Kong, S., Heo, J., Abidi, B., Paik, J., Abidi, M.: Recent advances in visual and infrared face recognition: a review. Comput. Vis. Image Underst. 97, 103–135 (2005)CrossRefGoogle Scholar
  18. 18.
    Abate, A., Nappi, M., Riccio, D., Sabatino, G.: 2D and 3D face recognition: a survey. Pattern Recognit. Lett. 28, 1885–1906 (2007)CrossRefGoogle Scholar
  19. 19.
    Zhang, X., Gao, Y.: Face recognition across pose: a review. Pattern Recognit. 42, 2876–2896 (2009)CrossRefGoogle Scholar
  20. 20.
    Seo, H., Milanfar, P.: Face verification using the LARK representation. IEEE Trans. Inf. Forensics Secur. 6, 1275–1286 (2011)CrossRefGoogle Scholar
  21. 21.
    Duda, R., Hart, P., Stork, D.: Pattern Classification, 2nd edn. Wiley, New York (2001)MATHGoogle Scholar
  22. 22.
    Seo, H., Milanfar, P.: Nonparametric detection and recognition of visual objects from a single example. In: Workshop on Defense Applications of Signal Processing (2009)Google Scholar
  23. 23.
    Seo, H.J., Milanfar, P.: Training-free, generic object detection using locally adaptive regression kernels. IEEE Trans. Pattern Anal. Mach. Intell. 32, 1688–1704 (2010)CrossRefGoogle Scholar
  24. 24.
    Shechtman, E., Irani, M.: Matching local self-similarities across images and videos. In: IEEE Conference Computer Vision Pattern Recognition, pp. 1–8 (2007)Google Scholar
  25. 25.
    Gonzalez, R., Woods, R.: Digital Image Processing, 2nd edn. Prentice Hall, New Jersey (2002)Google Scholar
  26. 26.
    Li, S. (ed.): Encyclopedia of Biometrics. Springer, New York (2009)Google Scholar
  27. 27.
    Canny, J.: A computational approach to edge detection. IEEE Trans. Pattern Anal. Mach. Intell. 8, 679–698 (1986)CrossRefGoogle Scholar
  28. 28.
    Burger, W., Burge, M.: Digital Image Processing: An Algorithmic Introduction Using Java. Springer, New York (2008)CrossRefGoogle Scholar
  29. 29.
    Schneider, P., Eberly, D.: Geometric Tools for Computer Graphics. Morgan Kaufmann, San Francisco (2003)Google Scholar
  30. 30.
    Schneider, J., Borlund, P.: Matrix comparison, part 1: motivation and important issues for measuring the resemblance between proximity measures or ordination results. J. Am. Soc. Inf. Sci. Technol. 58, 1586–1595 (2007)CrossRefGoogle Scholar
  31. 31.
    Huang, G., Ramesh, M., Berg, T., Learned-Miller, E.: Labeled faces in the wild: a database for studying face recognition in unconstrained environments. Retrieved 14 Nov 2012 from (2007)
  32. 32.
    Kumar, N., Berg, A., Belhumeur, P., Nayar, S.: Attribute and simile classifiers for face verification. In: Proceedings of the IEEE International Conference Computer Vision, pp. 365–372 (2009)Google Scholar
  33. 33.
    Bose, R.: Information Theory, Coding and Cryptography, 2nd edn. Tata McGraw-Hill, New Delhi (2008)Google Scholar
  34. 34.
    Viola, P., Wells, W.M.: Alignment by maximization of mutual information. In: 5th International Conference Computer Vision, pp. 16–23 (1995)Google Scholar
  35. 35.
    Tzimiropoulos, G., Zafeiriou S., Pantic, M.: Robust and efficient parametric face alignment. In: Proceedings of the International Conference Computer Vision, pp. 1847–1854 (2011)Google Scholar
  36. 36.
    Ojala, T., Pietikäinen, M., Mäenpää, T.: Multiresolution gray-scale and rotation invariant texture classification with local binary patterns. IEEE Trans. Pattern Anal. Mach. Intell. 24, 971–987 (2002)CrossRefGoogle Scholar
  37. 37.
    Bicego, M., Lagorio, A., Grosso, E., Tistarelli, M.: On the use of SIFT features for face authentication. In: Computer Vision and Pattern Recognition Workshop (2006)Google Scholar
  38. 38.
    Lowe, D.G.: Distinctive image features from scale-invariant keypoints. Int. J. Comput. Vis. 60, 91–110 (2004)CrossRefGoogle Scholar
  39. 39.
    Cheng, H., Liu, Z., Zheng, N., Yang, J.: A deformable local image descriptor. In: Proceedings of the IEEE Conference Computer Vision and Pattern Recognition, pp. 1–8 (2008)Google Scholar
  40. 40.
    Chen, J., Shan, S., He, C., Zhao, G., Pietikäinen, M., Chen, X., Gao, W.: WLD: a robust local image descriptor. IEEE Trans. Pattern Anal. Mach. Intell. 32, 1705–1720 (2010)CrossRefGoogle Scholar
  41. 41.
    Winkler, S.: Digital Video Quality: Vision Models and Metrics. Wiley, New Jersey (2005)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Marian Moise
    • 1
  • Xue Dong Yang
    • 1
  • Richard Dosselmann
    • 1
  1. 1.Department of Computer ScienceUniversity of ReginaReginaCanada

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