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Proceedings of International Conference on Computer Vision and Image Processing pp 475–485Cite as

Reassigned Time Frequency Distribution Based Face Recognition

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 460))

Abstract

In this work, we have designed a local descriptor based on the reassigned Stankovic time frequency distribution. The Stankovic distribution is one of the improved extensions of the well known Wigner Wille distribution. The reassignment of the Stankovic distribution allows us to obtain a more resolute distribution and hence is used to describe the region of interest in a better manner. The suitability of Stankovic distribution to describe the regions of interest is studied by considering face recognition problem. For a given face image, we have obtained key points using box filter response scale space and scale dependent regions around these key points are represented using the reassigned Stankovic time frequency distribution. Our experiments on the ORL, UMIST and YALE-B face image datasets have shown the suitability of the proposed descriptor for face recognition problem.

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References

  1. M. F. A. Abdullah, M. S. Sayeed, K. S. Muthu, H. K. Bashier, A. Azman, and S. Z. Ibrahim. (2014) ‘Face recognition with symmetric local graph structure (slgs)’. Expert Systems with Applications, Vol.41, No.14, pp.6131–6137.

    Google Scholar 

  2. F. Auger and P. Flandrin. (1995) ‘Improving the readability of time frequency and time-scale representations by the reassignment method’. IEEE Transactions on Signal Processing, Vol.43, No.5 pp.1068– 1089.

    Google Scholar 

  3. I. Djurovic and L. Stankovic. (1999) ‘The reassigned s-method’. In Telecommunications in Modern Satellite, Cable and Broadcasting Services, 1999. 4th International Conference on, Vol. 2, pp.464 467.

    Google Scholar 

  4. Z. Huang, W. Li, J. Wang, and T. Zhang. (2015) ‘Face recognition based on pixel-level and feature-level fusion of the toplevels wavelet sub-bands’. Information Fusion, vol.22, No. pp.95–104.

    Google Scholar 

  5. N. A. Krisshna, V. K. Deepak, K. Manikantan, and S. Ramachandran. (2014) ‘Face recognition using transform domain feature extraction and pso-based feature selection’. Applied Soft Computing, Vol.22, pp.141–161.

    Google Scholar 

  6. J. Lu, J. Zhao, and F. Cao. (2014) ‘Extended feed forward neural networks with random weights for face recognition’. Neurocomputing, Vol.136, pp.96–102.

    Google Scholar 

  7. F. A. P. Flandrin and E. Chassande-Mottin. (2002) ‘Time-frequency reassignment from principles to algorithms’. Applications in Time Frequency Signal Processing, Vol.12 No.1, pp.234 778.

    Google Scholar 

  8. D. Ramasubramanian and Y. Venkatesh. (2001) ‘Encoding and recognition of faces based on the human visual model and fDCTg’. Pattern Recognition, Vol.34, No.12, pp.2447–2458.

    Google Scholar 

  9. Z. Sun, J. Li, and C. Sun. (2014) ‘Kernel inverse fisher discriminant analysis for face recognition’. Neurocomputing, Vol.134, pp.4652.

    Google Scholar 

  10. M. Yang, L. Zhang, S. C. Shiu, and D. Zhang. (2013) ‘Gabor feature based robust representation and classification for face recognition with gabor occlusion dictionary’. Pattern Recognition, Vol.46, No.7, pp.1865–1878.

    Google Scholar 

  11. Rene Carmona, Wen-Liang Hwang, Bruno Torresani. ‘Practical Time-Frequency Analysis, Volume 9: Gabor and Wavelet Transforms, with an Implementation in S (Wavelet Analysis and Its Applications)’ 1st Edition

    Google Scholar 

  12. LjubiSa StankoviC, (1994) ‘A Method for Time-Frequency Analysis’. IEEE Transactions on Signal Processing, pp.225–229.

    Google Scholar 

  13. M. Agrawal, K. Konolige, and M. Blas, (2004) ‘CenSurE: Center Surround Extremas for Realtime Feature Detection and Matching’. Springer, pp.102 115.

    Google Scholar 

  14. Franois Auger, Patrick Flandrin, Paulo Gonalvs, Olivier Lemoine, (1996) ‘Time-Frequency Toolbox’, CNRS (France), Rice University (USA).

    Google Scholar 

  15. F. S. Samaria and F. S. Samaria *t and A.C. Harter and Old Addenbrooke’s Site, 1994 ‘Parameterisation of a Stochastic Model for Human Face Identification’.

    Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Computer Science, Mangalore University, Mangalagangothri, 574199, Karnataka, India

    B. H. Shekar & D. S. Rajesh

Authors
  1. B. H. Shekar
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  2. D. S. Rajesh
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Corresponding author

Correspondence to B. H. Shekar .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, India

    Balasubramanian Raman

  2. Department of Mathematics, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, India

    Sanjeev Kumar

  3. Department of Computer Science and Engineering, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, India

    Partha Pratim Roy

  4. Department of Computer Science and Engineering, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, India

    Debashis Sen

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© 2017 Springer Science+Business Media Singapore

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Cite this paper

Shekar, B.H., Rajesh, D.S. (2017). Reassigned Time Frequency Distribution Based Face Recognition. In: Raman, B., Kumar, S., Roy, P., Sen, D. (eds) Proceedings of International Conference on Computer Vision and Image Processing. Advances in Intelligent Systems and Computing, vol 460. Springer, Singapore. https://doi.org/10.1007/978-981-10-2107-7_43

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  • DOI: https://doi.org/10.1007/978-981-10-2107-7_43

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-2106-0

  • Online ISBN: 978-981-10-2107-7

  • eBook Packages: EngineeringEngineering (R0)

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