Feature Line-Based Local Discriminant Analysis for Image Feature Extraction

  • Jeng-Shyang Pan
  • Shu-Chuan Chu
  • Lijun Yan
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 298)

Abstract

In this paper, a novel image feature extraction algorithm, entitled Feature Line-based Local Discriminant Analysis (FLLDA), is proposed. FLLDA is a subspace learning algorithm based on Feature Line (FL) metric. FL metric is used for the evaluation of the local within-class scatter and local between class scatter in the proposed FLLDA approach. The Experimental results on COIL20 image database confirm the effectiveness of the proposed algorithm.

Keywords

Feature Extraction Image Classification Nearest Feature Line 

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References

  1. 1.
    Belhumenur, P., Hepanha, J., Kriegman, D.: Eigenfaces vs. Fisherface: Recognition using class specific linear projection. IEEE Transactions on Pattern Analysis Machine and Intelligence 19(7), 711–720 (1997)CrossRefGoogle Scholar
  2. 2.
    He, X., Yan, S., Hu, Y., Niyogi, P., Zhang, H.: Face recognition using laplacianface. IEEE Transactions on Pattern Analysis Machine and Intelligence 27(3), 328–340 (2005)CrossRefGoogle Scholar
  3. 3.
    Kong, A., Zhang, D., Kamel, M.: A survey of palmprint recognition. Pattern Recognition 42(7), 1408–1418 (2009)CrossRefGoogle Scholar
  4. 4.
    Li, J., Gao, H.: Sparse data-dependent kernel principal component analysis based on least squares support vector machine for feature extraction and recognition. Neural Computing and Applications 21(8), 1971–1980 (2012)CrossRefGoogle Scholar
  5. 5.
    Li, J., Pan, J., Chu, S.: Kernel class-wise locality preserving projection. Information Sciences 178(7), 1825–1835 (2008)CrossRefMATHGoogle Scholar
  6. 6.
    Li, J.B., Chu, S.C., Pan, J.S., Jain, L.C.: Multiple viewpoints based overview for face recognition. Journal of Information Hiding and Multimedia Signal Processing 3(4), 352–369 (2012)Google Scholar
  7. 7.
    Li, S., Lu, J.: Face recognition using the nearest feature line method. IEEE Transactions on Neural Networks 10(2), 439–443 (1999)CrossRefGoogle Scholar
  8. 8.
    Lu, J., Tan, Y.P.: Uncorrelated discriminant nearest feature line analysis for face recognition. IEEE Signal Processing Letters 17(2), 185–188 (2010)Google Scholar
  9. 9.
    Martinez, A.M., Kak, A.: Pca versus lda. IEEE Transactions on Pattern Analysis and Machine Intelligence 23(2), 228–233 (2001)CrossRefGoogle Scholar
  10. 10.
    Nene, S.A., Nayar, S.K., Murase, H.: Columbia object image library (coil-20). In: Technical Report CUCS-005-96 (1996)Google Scholar
  11. 11.
    Pang, Y., Yuan, Y., Li, X.: Nearest neighbour line nonparametric discriminant analysis for feature extraction. Electron. Lett. 42(12), 679–680 (2006)CrossRefGoogle Scholar
  12. 12.
    Roweis, S.: Em algorithms for pca and spca. In: Advances in Neural Information Processing Systems, pp. 626–632. MIT Press (1998)Google Scholar
  13. 13.
    Turk, M., Pentland, A.: Eigenfaces for recognition. J. Cogn. Neurosci. 3(1), 71–86 (1991)CrossRefGoogle Scholar
  14. 14.
    Xu, Y., Zhang, D.: Represent and fuse bimodal biometric images at the feature fevel: Complex-matrix-based fusion scheme. Optical Engineering 49(3), 037002–037002-6(2010)Google Scholar
  15. 15.
    Xu, Y., Zhang, D., Jin, Z., Li, M., Yang, J.: A fast kernel-based nonlinear discriminant analysis for multi-class problems. Pattern Recognition 39(6), 1026–1033 (2006)CrossRefMATHGoogle Scholar
  16. 16.
    Yan, L., Zheng, W., Chu, S., Roddick, J.: Neighborhood discriminant nearest feature line analysis for face recognition. Journal of Internet Technology 14(1), 344–347 (2013)Google Scholar
  17. 17.
    Zheng, Y., Yang, J., Yang, J., Wu, X., Jin, Z.: Nearest neighbour line nonparametric discriminant analysis for feature extraction. Electron. Lett. 42(12), 679–680 (2006)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Jeng-Shyang Pan
    • 1
  • Shu-Chuan Chu
    • 2
  • Lijun Yan
    • 1
  1. 1.Harbin Institute of Technology Shenzhen Graduate SchoolXili University TownNanShanChina
  2. 2.School of Computer Science,Engineering and MathematicsFlinders University of South AustraliaAdelaide, South AustraliaAustralia

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