2005
DOI: 10.1088/1742-6596/13/1/098
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Optimised reflection imaging for surface roughness analysis using confocal laser scanning microscopy and height encoded image processing

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Cited by 12 publications
(5 citation statements)
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“…This technique has been used widely in different fields due to the capability of CLSM to scan samples at different depths, reduce noise, and provide high resolution images. [32,33] Briefly, surface data were collected from CLSM with resolution of 512 Â 512 pixels, a pixel size of 1.51 mm, and …”
Section: Characterization Methodsmentioning
confidence: 99%
“…This technique has been used widely in different fields due to the capability of CLSM to scan samples at different depths, reduce noise, and provide high resolution images. [32,33] Briefly, surface data were collected from CLSM with resolution of 512 Â 512 pixels, a pixel size of 1.51 mm, and …”
Section: Characterization Methodsmentioning
confidence: 99%
“…Surface roughness was measured using confocal laser scanning microscopy (CLSM) (Leica TCS SP5) to scan each structure's surface. This technique has been used widely in different fields due to the capability of CLSM to scan samples at different depths, reduce noise, and provide high resolution images 32, 33. Briefly, surface data were collected from CLSM with resolution of 512 × 512 pixels, a pixel size of 1.51 µm, and distance between images of 0.99 µm.…”
Section: Methodsmentioning
confidence: 99%
“…In addition, the high spatial resolution of confocal microscopy allows you to precisely reconstruct the 3D surface of the sample without pre-treatment of the sample. Roughness parameters can be calculated with various algorithms based on the surface map acquired from confocal microscopy [156], such as calculating average roughness, measuring variance or asymmetry of the amplitude distribution function, evaluating spikiness in the profile [157], calculating the arithmetic mean deviation of all surface height values [158], and evaluating the actual surface area to the nominal surface area [159]. Surface roughness analysis has been widely used to characterize the texture of the surfaces to evaluate fractures and cracks in material science [159].…”
Section: Surface Roughnessmentioning
confidence: 99%