Monitoring defects of a moving metallic surface through Tsallis entropic segmentation

M.R.B. Dias, A.O. Castro Junior, C.P. Dias, S.A. de Carvalho, J.A.O. Huguenin and L. da Silva

Physica A: Statistical Mechanics and its Applications, 2019, vol. 534, issue C

Abstract: Speckle patterns can be generated by the scattering of a laser light in a rough surface. Digital images of speckle patterns can be related with surface roughness. In this paper the Tsallis entropy was used to determine the threshold of the entropic segmentation on a digital image of speckle pattern. We show that it is a powerful tool to discern defects, which can be inferred as roughness variation, in a moving metallic sample. Furthermore, we investigated the results yielded by two laser wavelengths in order to verify the influence of this parameter.

Keywords: Speckle pattern; Roughness; Tsallis entropy; Entropic segmentation; Moving sample (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:534:y:2019:i:c:s0378437119312610

DOI: 10.1016/j.physa.2019.122175

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