Skip to main content
SpringerLink
Log in

An Improved Vehicle Logo Recognition Using a Classifier Ensemble Based on Pattern Tensor Representation and Decomposition

  • Published:
New Generation Computing Aims and scope Submit manuscript

Abstract

The paper presents a vehicle logo recognition system based on novel combination of tensor based feature extraction and ensemble of tensor subspace classifiers. Each originally two-dimensional vehicle logotype is transformed to a three-dimensional feature tensor applying the extended structural tensor method. All such exemplary logo-tensors which correspond to a single class are stacked to form a 4D logo-class-tensor. Decomposing each 4D logo-class-tensor into the orthogonal tensor subspace allows classification of unknown logotypes. The proposed system allows reliable vehicle logo recognition in real conditions as shown by experiments.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Bigün, J., Granlund, G. H., Wiklund, J., “Multidimensional Orientation Estimation with Applications to Texture Analysis and Optical Flow,” IEEE PAMI, 13, 8, pp. 775–790, 1991.

  2. Brox, T., Boomgaard van den, R., Lauze, F., Weijer van de, J., Weickert, J., Mrázek, P., Kornprobst, P., “Adaptive Structure Tensors and their Applications, in Visualization and Processing of Tensor Fields (Weickert, J., Hagen, H. ed.), Springer, pp. 17–47, 2006.

  3. Bugaj, M., Cyganek, B., “GPU Based Computation of the Structural Tensor for Real-Time Figure Detection,” in Proc. of the 20th International Conference on Computer Graphics, Visualization and Computer Vision (WSCG’12), Czech Republic, 2012.

  4. Cyganek, B., Object Detection and Recognition in Digital Images: Theory and Practice, Wiley, 2013.

  5. Cyganek, B., “Object Recognition with the Higher-Order Singular Value Decomposition of the Multi-Dimensional Prototype Tensors,” 3rd Computer Science On-line Conference (CSOC 2014). Advances in Intelligent Systems and Computing, Springer, pp. 395–405, 2014.

  6. Cyganek, B., Woźniak, M., “Vehicle Logo Recognition with an Ensemble of Classifiers,” ACIIDS 2014, Part II, LNAI 8398 (Nguyen, N. T. et al. eds.), pp. 117–126, 2014.

  7. Dai, S., Huang, H., Gao, Z., “Vehicle-logo recognition method based on Tchebichef moment invariants and SVM,” Software Engineering, WCSE’09, pp. 18–21, 2009.

  8. Jähne, B., Digital Image Processing (6th edition), Springer-Verlag, 2005.

  9. Huber P.J.: Robust statistics, John Wiley, New York (1981)

    Book  MATH  Google Scholar 

  10. Ki, Y., Baik, D., “Vehicle-classification algorithm for single-loop detectors using neural networks,” Vehicular Technology, IEEE Transactions on, 55, 6, pp. 1704–1711, 2006.

  11. Kolda, T. G., Bader, B. W., “Tensor Decompositions and Applications,” SIAM Review, pp. 455–500, 2008.

  12. Krawczyk, B., Woźniak, M., Herrera, F., “On the Usefulness of One-Class Classifier Ensembles for Decomposition of Multi-Class Problems,” Elsevier Pattern Recognition, doi:10.1016/j.patcog.2015.06.001, 2015.

  13. Krawczyk, B., “One-class classifier ensemble pruning and weighting with firefly algorithm,” Neurocomputing, 150, Elsevier, pp. 490–500, 2015.

  14. Lathauwer, de L., “Signal Processing Based on Multilinear Algebra,” Ph. D. dissertation, Katholieke Universiteit Leuven, 1997.

  15. Lathauwer de L., Moor de B., Vandewalle J., “A Multilinear Singular Value Decomposition,” SIAM Journal of Matrix Analysis and Applications, 21(4), 1253–1278 (2000)

    Article  MATH  Google Scholar 

  16. Leys, C., Ley, C., Klein, O., Bernard, P., Licata, L., “Detecting outliers: Do not use standard deviation around the mean, use absolute deviation around the median,” Journal of Experimental Social Psychology, 49, 4, pp. 764–766, July 2013.

  17. Medialab LPR database, http://www.medialab.ntua.gr/research/LPRdatabas. html, 2015.

  18. Petrovic, V. S., Cootes, T. F., “Analysis of features for rigid structure vehicle type recognition,” in Proc. BMVC, 2004.

  19. Psyllos, A. P., Anagnostopoulos, C.-N. E., Kayafas, E., “Vehicle logo recognition using a sift-based enhanced matching scheme,” IEEE ITS, 11, 2, pp. 322–328, 2010.

  20. Psyllos, A., Anagnostopoulos, C., Kayafas, E., “Vehicle model recognition from frontal view image measurements,” Computer Standards & Interfaces, 33, 2, pp. 142–151, 2011.

  21. Psyllos, A., Anagnostopoulos, C.-N., Kayafas, E., “M-SIFT: A new method for Vehicle Logo Recognition, 2012 IEEE International Conference on Vehicular Electronics and Safety, Istanbul, Turkey, 2012.

  22. Savas B., Eldén L., “Handwritten digit classification using higher order singular value decomposition,” Pattern Recognition, 40, 993–1003 (2007)

    Article  MATH  Google Scholar 

  23. Sulehria, H., Zhang, Y., “Vehicle logo recognition using mathematical morphology,” Proc. of the 6th WSEAS Intl Conf. on Telecommunications and Informatics, 2007.

  24. Turk, M., Pentland, A., “Eigenfaces for recognition,” Journal of Cognitive Neuroscience, 3, 1, pp. 71–86, 1991.

  25. Luis-García, R., Deriche, R., Rousson, M., Alberola-López, C., “Tensor Processing for Texture and Colour Segmentation,” LNCS, 3540, pp. 1117–1127, 2005.

  26. Meyer, C.D., Matrix Analysis and Applied Linear Algebra, SIAM, 2000.

  27. Perona, P., Malik, J., “Scale-Space and Edge Detection Using Anisotropic Diffusion,” IEEE Transactions on Pattern Analysis and Machine Intelligence, 12, 7, pp. 629–639, July 1990.

  28. Sapiro, G., Geometric Partial Differential Equations and Image Analysis, Cambridge University Press, 2001.

  29. Woźniak, M., Grana, M, Corchado, E., “A survey of multiple classifier systems as hybrid systems,” Information Fusion, 16, pp. 3–17, March 2014.

Download references

Author information

Authors and Affiliations

  1. AGH University of Science and Technology, Al. Mickiewicza 30, 30-059, Kraków, Poland

    Bogusław Cyganek

  2. Wrocław University of Technology, Wybrzeże Wyspiańskiego 27, 50-370, Wrocław, Poland

    Michał Woźniak

Authors
  1. Bogusław Cyganek
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Michał Woźniak
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Bogusław Cyganek.

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Cyganek, B., Woźniak, M. An Improved Vehicle Logo Recognition Using a Classifier Ensemble Based on Pattern Tensor Representation and Decomposition. New Gener. Comput. 33, 389–408 (2015). https://doi.org/10.1007/s00354-015-0403-3

Download citation

  • Received:

  • Revised:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00354-015-0403-3

Keywords

Search

Navigation