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An adaptive tensor voting algorithm combined with texture spectrum

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Abstract

An adaptive tensor voting algorithm combined with texture spectrum is proposed. The image texture spectrum is used to get the adaptive scale parameter of voting field. Then the texture information modifies both the attenuation coefficient and the attenuation field so that we can use this algorithm to create more significant and correct structures in the original image according to the human visual perception. At the same time, the proposed method can improve the edge extraction quality, which includes decreasing the flocculent region efficiently and making image clear. In the experiment for extracting pavement cracks, the original pavement image is processed by the proposed method which is combined with the significant curve feature threshold procedure, and the resulted image displays the faint crack signals submerged in the complicated background efficiently and clearly.

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Author information

Authors and Affiliations

  1. School of Information and Electrical Engineering, Ludong University, Yantai, 264025, China

    Gang Wang  (王刚), Qing-tang Su  (苏庆堂), Gao-huan Lü  (吕高焕), Xiao-feng Zhang  (张小峰) & Yu-huan Liu  (刘玉环)

  2. School of Science, Nanjing University of Science & Technology, Nanjing, 210094, China

    Gang Wang  (王刚) & An-zhi He  (贺安之)

Authors
  1. Gang Wang  (王刚)
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  2. Qing-tang Su  (苏庆堂)
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  3. Gao-huan Lü  (吕高焕)
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  4. Xiao-feng Zhang  (张小峰)
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  5. Yu-huan Liu  (刘玉环)
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  6. An-zhi He  (贺安之)
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Corresponding author

Correspondence to Gang Wang  (王刚).

Additional information

This work has been supported by the National Natural Science Foundation of China (No.61471185), the Joint Special Fund of Shandong Province Natural Science Foundation (No.ZR2013FL008), and the Project of Shandong Province Higher Educational Science and Technology Program (No.J14LN20).

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Cite this article

Wang, G., Su, Qt., Lü, Gh. et al. An adaptive tensor voting algorithm combined with texture spectrum. Optoelectron. Lett. 11, 73–76 (2015). https://doi.org/10.1007/s11801-015-4174-3

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  • DOI: https://doi.org/10.1007/s11801-015-4174-3

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