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A novel image matching algorithm based on sliding histograms of oriented gradients

Abstract

A novel algorithm for image matching based on recursive calculation of histograms of oriented gradients over several circular sliding windows and pyramidal image decomposition is presented. The algorithm gives good results for geometrically distorted and scaled scene images. The results of computer simulation obtained with the proposed algorithm are compared to those of available algorithms in terms of matching accuracy and processing time.

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References

  1. D. G. Lowe, “Object recognition from local scale-invariant features,” in Proc. 7th Int. Conf. on Computer Vision, Crete, 1999 (IEEE, New York, 1999), Vol. 2, pp. 1150–1157.

    Google Scholar 

  2. H. Bay, A. Ess, T. Tuytelaars, and L. Van Gool, “SURF: Speeded Up Robust Features,” Comput. Vis. Image Underst. 110, 346–359 (2008).

    Article  Google Scholar 

  3. E. Rublee, V. Rabaud, K. Konolige, and G. Bradski, “ORB: an efficient alternative to SIFT or SURF,” in Proc. IEEE Int. Conf. on Computer Vision, Barcelona, 2011 (IEEE, New York, 2011), pp. 2564–2571.

    Chapter  Google Scholar 

  4. M. Calonder, V. Lepetit, C. Strecha, and P. Fua, “BRIEF: binary robust independent elementary features,” in Proc. 11th Eur. Conf. on Computer Vision. (ECCV’10), Hersonissos Heraklion Crete, Greece, 2010 (Springer-Verlag, 2010), pp. 778–792.

    Google Scholar 

  5. R. Ortiz, “FREAK: Fast Retina Keypoint,” in Proc. IEEE Conf. on Computer Vision and Pattern Recognition, CVPR’12, Providence, RI, June, 2012 (IEEE, New York, 2012), pp. 510–517.

    Google Scholar 

  6. V. H. Díaz-Ramírez and V. Kober, “Adaptive phaseinput joint transform correlator,” Appl. Opt. 46, 6543–6551 (2007).

    Article  Google Scholar 

  7. Y. Ouerhani, M. Jridi, and A. Alfalou, and C. Brosseau, “Optimized preprocessing input plane GPU implementation of an optical face recognition technique using a segmented phase only composite filter,” Opt. Commun. 289, 33–44 (2013).

    Article  Google Scholar 

  8. K. L. Rice, T. M. Taha, A. M. Chowdhury, A. A. S. Awwal, and D. L. Woodard, “Design and acceleration of phase-only filter-based optical pattern recognition for fingerprint identification,” Opt. Eng. 48(11), 117–206 (2009).

    Google Scholar 

  9. B. A. Zalesky and P. V. Lukashevich, “Scale invariant algorithm to match regions on aero or satellite images,” Proc. Pattern Recogn. Inf. Process. 11, 25–30 (2011).

    Google Scholar 

  10. N. Dalal and B. Triggs, “Histograms of oriented gradients for human detection,” Comput. Vis. Pattern Recogn. 1, 886–893 (2005).

    Google Scholar 

  11. W. K. Pratt, Digital Image Processing (Wiley, New York, 2007).

    Book  Google Scholar 

  12. T. Lindeberg, “Scale-space theory: A basic tool for analysis structures at different scales,” J. Appl. Statis. 21, 225–270 (1994).

    Article  Google Scholar 

  13. B. Liu and A. Zaccarin, “New fast algorithms for the estimation of block motion vectors,” IEEE Trans. Circuits Syst. Video Technol. 3, 148–157 (1993).

    Article  Google Scholar 

  14. J. M. Geusebroek, G. J. Burghouts, and A. W. M. Smeulders, The Amsterdam library of object images, International Journal of Computer Vision, 2005, vol. 61, no. 1, pp. 103–112, http://staff.science.uva.nl/aloi/

    Article  Google Scholar 

  15. Li X. Rong and V. P. Jilkov, “Survey of maneuvering target tracking. Part I: Dynamic models,” IEEE Trans. Aerosp. Electron. Syst. 39, 1333–1364 (2003).

    Article  Google Scholar 

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Correspondence to V. N. Karnaukhov.

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Original Russian Text © D. Miramontes-Jaramillo, V.I. Kober, V.H. Díaz-Ramírez, V.N. Karnaukhov, 2014, published in Informatsionnye Protsessy, 2014, Vol. 14, No. 1, pp. 56–63.

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Miramontes-Jaramillo, D., Kober, V.I., Díaz-Ramírez, V.H. et al. A novel image matching algorithm based on sliding histograms of oriented gradients. J. Commun. Technol. Electron. 59, 1446–1450 (2014). https://doi.org/10.1134/S1064226914120146

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  • DOI: https://doi.org/10.1134/S1064226914120146

Keywords

  • image matching
  • fast algorithm
  • histogram of oriented gradients
  • circular window