An adaptive tensor voting algorithm combined with texture spectrum

Gang Wang; Qing-tang Su; Gao-huan Lü; Xiao-feng Zhang; Yu-huan Liu; An-zhi He

doi:10.1007/s11801-015-4174-3

Optoelectronics Letters ›› , Vol. 11 ›› Issue (1) : 73-76. DOI: 10.1007/s11801-015-4174-3

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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.

Keywords

Texture Information / Attenuation Function / Human Visual Perception / Tensor Vote / Attenuation Field

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Gang Wang, Qing-tang Su, Gao-huan Lü, Xiao-feng Zhang, Yu-huan Liu, An-zhi He. An adaptive tensor voting algorithm combined with texture spectrum. Optoelectronics Letters, , 11(1): 73‒76 https://doi.org/10.1007/s11801-015-4174-3

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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).