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Localized Radon Polar Harmonic Transform (LRPHT) Based Rotation Invariant Analysis of Textured Images

Author

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  • Satya P. Singh

    (Electronics Engineering Department, Galgotias College of Engineering and Technology, Greater Noida, India)

  • Shabana Urooj

    (School of Engineering, Gautam Buddha University, Greater Noida, India)

Abstract

In this paper, the authors propose a method to analyze and capture the information from texture regardless their geometric deformation. Input image is transformed to radon space and multiresolution is achieved within the radon space using Gaussian derivative wavelet. The transformed image is applied to the polar harmonic transform (PHT). The proposed method is tested against additive Gaussian noise and impulse noise with different rotations. A k- nearest neighbor classifier is employed to classify the texture. To test and evaluate correct classification percentage of the method, several sets of texture are evaluated with different rotation angle under different noisy condition. Experimental results show superiority of method in comparison to recent invariant texture analysis method.

Suggested Citation

  • Satya P. Singh & Shabana Urooj, 2015. "Localized Radon Polar Harmonic Transform (LRPHT) Based Rotation Invariant Analysis of Textured Images," International Journal of System Dynamics Applications (IJSDA), IGI Global, vol. 4(2), pages 21-41, April.
  • Handle: RePEc:igg:jsda00:v:4:y:2015:i:2:p:21-41
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