Tsallis threshold analysis of digital speckle patterns generated by rough surfaces

• We use entropic segmentation on digital speckle pattern images acquired in the diffraction plane.
• We relate threshold values obtained with Tsallis entropic segmentation with the surface roughness of metallic samples.
• We propose a new method for characterizing rough surfaces with Tsallis entropic segmentation.

In this work we report on a study of entropic threshold of digital speckle patterns images produced by rough surfaces using Tsallis entropy. The speckle pattern images were obtained in the diffraction plane at the normal direction and they are the outcome of the incidence of a laser beam in the rough metallic surfaces. The speckle pattern images were segmented in order to verify the sensitivity of the optimal Tsallis entropic threshold value as a function of the surface roughness. We show that the surface roughness can be sensed and tuned by this method.