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Color image analysis via Racah moments

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
In this research, Racah moments color image descriptors are investigated. Channels separation for color images were involved in RGB color space, and Racah moments from each channel were computed individually. In experiments, we have performed the color image reconstructions from different color channels and various orders of Racah moments. Our experimental results have demonstrated that, by applying Racah moments, color images can be completely reconstructed without any information loss. We have also discovered that the individual set of Racah moments will uniquely describe the color image features, while the lower and higher orders of Racah moments will preserve more of features from the bottom right and top left regions of a color image, respectively.
Słowa kluczowe
Rocznik
Strony
8--18
Opis fizyczny
Bibliogr. 16 poz., rys., tab., wz.
Twórcy
autor
  • Department of Applied Computer Science, The University of Winnipeg, Canada
autor
  • Department of Applied Computer Science, The University of Winnipeg, Canada
Bibliografia
  • [1] L.V. Gool, F. Mindru, T. Tuytelaars and T. Moons. Moment invariants for recognition under changing viewpoint and illumination. Comput. Vis. Image Und., pages 3–27, 2004.
  • [2] T. Moons, F. Mindru and L.V. Gool. Color-based moment invariants for the viewpoint and illuminati on independent recognition of planar color patterns. In Int. Conf. Advances in Pattern Recognition (ICAPR¡¯98), pages 113–122, 1998.
  • [3] J. Flusser, T. Suk, and B. Zitova. Moments and moment invariants in pattern recognition. John Wiley & Sons, Ltd, 2009.
  • [4] M. K. Hu. Visual pattern recognition by moment invariants. IRE Transactions on Information Theory, 8:179–187, 1962.
  • [5] R. Mukundan and K.R. Ramakrishnan. Moment Functions in Image Analysis - Theory and Applications. World Scientific, 1998.
  • [6] M. Pawlak. Image Analysis by Moments: Reconstrcution and Aomputational Aspects. Oficyna Wydawnicza Politechniki WrocLawskiej, WrocLaw, 2006.
  • [7] Y. Pew-Thian, P. Raveendran, and O. Seng-Huat. Image analysis by krawtchouk moments. Image Processing, IEEE Transactions on, 12(11):1367–1377, 2003.
  • [8] S. H. Ong, R. Mukundan and P. A. Lee. Discrete vs. continuous orthogonal moments for image analysis. International. Conf. on Imaging Science, Systems and Technology-CISST’01, pages 23–29, 2001.
  • [9] M. Ramakrishnan, Ong. S. H, and L. Poh Aun. Image analysis by tchebichef moments. Image Processing, IEEE Transactions on, 10(9):1357–1364, 2001.
  • [10] S. J. Sangwine. Fourier transforms of colour images using quaternion or hypercomplex numbers. Electron, Lett., pages 1979–1980, 1996.
  • [11] T. Suk and J. Flusser. Affine moment invariants of color images. In CAIP 2009, LNCS5702, pages 334–341, 2009.
  • [12] Y. Wu and S. Liao. Chinese characters recognition via racah moments. Audio, Language and Image Processing (ICALIP), pages 691–694, 2014.
  • [13] Y. Wu and S. Liao. Image reconstruction from racah moments. Accepted by The 29th Annual IEEE Canadian Conference on Electrical and Computer Engineering (CCECE 2016), 2016.
  • [14] C. C. Chang, Y.K. Chan. A color image retrieval method based on color moment and color ariance of adjacent pixels. Int. J. Pattern Recognition. Artif. Intell., 16:113–125, 2002.
  • [15] X. Zhang and S. Liao. Color image reconstruction from charlier moments. Journal of Theoretical and Applied Computer Science, page in press, 2016.
  • [16] H. Zhu, H. Shu, J. Liang, L. Luo, , and J.-L. Coatrieux. Image analysis by discrete orthogonal racah moments. Signal Processing, 87(4):687–708, 2007.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-32aac02e-29dc-4ec9-8487-4d7549dacbfc
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