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CWMA: Circular Window Matching Algorithm

  • Daniel Miramontes-Jaramillo
  • Vitaly Kober
  • Víctor Hugo Díaz-Ramírez
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8258)

Abstract

Various vision applications exploit matching algorithms to locate a target object in a scene image. A new fast matching algorithm based on recursive calculation of oriented gradient histograms over several circular sliding windows is presented. In order to speed up the algorithm pyramidal image decomposition technique and parallel implementation with modern multicore processors are utilized. The proposed fast algorithm yields a good invariance performance for both in-plane and out-of-plane rotations of a scene image. Computer results obtained with the proposed algorithm are presented and compared with those of common algorithms in terms of matching accuracy and processing time.

Keywords

Scale Invariant Feature Transform Scene Image Match Accuracy Cyclic Shift Recursive Calculation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. 1.
    Lowe, D.G.: Object recognition from local scale-invariant features. In: Proc. Int. Conference on Computer Vision, vol. 2, pp. 1150–1157 (1999)Google Scholar
  2. 2.
    Bay, H., Ess, A., Tuytelaars, T., Van Gool, L.: SURF: Speeded Up Robust Features. Comput. Vis. Image Underst. 110(3), 346–359 (2008)CrossRefGoogle Scholar
  3. 3.
    Calonder, M., Lepetit, V., Strecha, C., Fua, P.: BRIEF: Binary robust independent elementary features. In: Daniilidis, K., Maragos, P., Paragios, N. (eds.) ECCV 2010, Part IV. LNCS, vol. 6314, pp. 778–792. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  4. 4.
    Ortiz, R.: FREAK: Fast Retina Keypoint. In: Proc. of the 2012 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2012, pp. 510–517 (2012)Google Scholar
  5. 5.
    Liao, C., Wang, G., Miao, Q., Wang, Z., Shi, C., Lin, X.: DSP-Based Parallel Implementation of Speeded-Up Robust Features. IEICE Trans. on Information and Systems E94-D(4), 930–933 (2011)CrossRefGoogle Scholar
  6. 6.
    Manzurv, T., Zeller, J., Serati, S.: Optical correlator based target detection, recognition, classification, and tracking. Appl. Opt. 51, 4976–4983 (2012)CrossRefGoogle Scholar
  7. 7.
    Ouerhani, Y., Jridi, M., Alfalou, A., Brosseau, C.: Optimized preprocessing input plane GPU implementation of an optical face recognition technique using a segmented phase only composite filter. Opt. Comm. 289, 33–44 (2013)CrossRefGoogle Scholar
  8. 8.
    Diaz-Ramirez, V.H., Kober, V.: Adaptive phase-input joint transform correlator. Appl. Opt. 46(26), 6543–6551 (2007)CrossRefGoogle Scholar
  9. 9.
    Sanders, J., Kandrot, E.: CUDA by Example: An Introduction to General-Purpose GPU Programming. Addison-Wesley Professional (2010)Google Scholar
  10. 10.
    Rice, K.L., Taha, T.M., Chowdhury, A.M., Awwal, A.A.S., Woodard, D.L.: Design and acceleration of phase-only filter-based optical pattern recognition for fingerprint identification. Optical Engineering 48(11), 117–206 (2009)Google Scholar
  11. 11.
    Zalesky, B.A., Lukashevich, P.V.: Scale Invariant Algorithm to Match Regions on Aero or Satellite Images. In: Proc. Pattern Recognition and Information Processing, vol. 11, pp. 25–30 (2011)Google Scholar
  12. 12.
    Dalal, N., Triggs, B.: Histograms of Oriented Gradients for Human Detection. Computer Vision and Pattern Recognition 1, 886–893 (2005)Google Scholar
  13. 13.
    Pratt, W.K.: Digital Image Processing. John Wiley & Sons (2007)Google Scholar
  14. 14.
    López-Martınez, J.L., Kober, V.: Fast image restoration algorithm based on camera microscanning. In: Proc. SPIE, vol. 7443, pp. 744310–744315 (2009)Google Scholar
  15. 15.
    Geusebroek, J.M., Burghouts, G.J., Smeulders, A.W.M.: The Amsterdam library of object images. Int. J. Computer Vision. 61(1), 103–112 (2005), http://staff.science.uva.nl/~aloi/ CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Daniel Miramontes-Jaramillo
    • 1
  • Vitaly Kober
    • 1
  • Víctor Hugo Díaz-Ramírez
    • 2
  1. 1.CICESEEnsenadaMéxico
  2. 2.CITEDI-IPNTijuanaMéxico

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