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Adaptive Fractional Differentiation Harris Corner Detection Algorithm for Vision Measurement of Surface Roughness

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  • Rui-Yin Tang
  • Zhou-Mo Zeng

Abstract

The Harris algorithm via fractional order derivative (the adaptive fractional differentiation Harris corner detection algorithm), which adaptively adjusts the fractal dimension parameter, has been investigated for an analysis of image processing relevant to surface roughness by vision measurements. The comparative experiments indicate that the algorithm allows the edge information in the high frequency areas to be enhanced, thus overcoming shortcomings. The algorithm permits real‐time measurements of surface roughness to be performed with high precision, superior to the conventional Harris algorithm.

Suggested Citation

  • Rui-Yin Tang & Zhou-Mo Zeng, 2014. "Adaptive Fractional Differentiation Harris Corner Detection Algorithm for Vision Measurement of Surface Roughness," Advances in Mathematical Physics, John Wiley & Sons, vol. 2014(1).
    • Handle: RePEc:wly:jnlamp:v:2014:y:2014:i:1:n:494237
    DOI: 10.1155/2014/494237
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    References listed on IDEAS

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    1. J. A. Tenreiro Machado & Alexandra M. S. F. Galhano & Juan J. Trujillo, 2014. "On development of fractional calculus during the last fifty years," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(1), pages 577-582, January.
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