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Selection of multiresolution rotationally invariant moments for image recognition

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  • Rodtook, A.
  • Makhanov, S.S.

Abstract

We propose multiresolution filter bank techniques to construct rotationally invariant moments. The multiresolution pyramid motivates a simple but efficient feature selection procedure based on a combination of a pruning algorithm, a new version of the Apriori mining techniques and partially supervised fuzzy C-mean clustering. The recognition accuracy of the proposed techniques has been tested with the reference to conventional methods. The numerical experiments, with more than 50,000 images, demonstrate an accuracy increase ranging from 5% to 27% depending on the noise level.

Suggested Citation

  • Rodtook, A. & Makhanov, S.S., 2009. "Selection of multiresolution rotationally invariant moments for image recognition," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(8), pages 2458-2475.
    • Handle: RePEc:eee:matcom:v:79:y:2009:i:8:p:2458-2475
    DOI: 10.1016/j.matcom.2009.01.016
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    References listed on IDEAS

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    1. Richard Hathaway & James Bezdek, 1988. "Recent convergence results for the fuzzy c-means clustering algorithms," Journal of Classification, Springer;The Classification Society, vol. 5(2), pages 237-247, September.
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