Non-contact surface roughness measurement of blasted specimens using machine vision technique

This article describes non-contact surface roughness measurement for shot and grit blasted specimens. A simple machine vision algorithm was proposed for determining ten-point mean roughness (Rz) of a specimen after shot and grit blasting. Surfaces cleaned with different blast abrasives were captured by a microscope. Binary images were then created by using Otsu's thresholding method. On the binary image, bright regions were selected, associated with specular reflection of light. The average size of selected regions was calculated in this proposed method. It was found that the average size has a linear relation with ten-point mean roughness of both shot and grit blasted surfaces. It was also identified that the parameter of a linear regression for shot blasting is different from that for grit blasting. On the basis of the relation, it is possible to determine the ten-point mean roughness of a blasted surface with a captured surface image.

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Publication Details

Journal
International Journal of Surface Science and Engineering
Published
2025-01-01
DOI
https://doi.org/10.1504/ijsurfse.2025.144836
Primary Topic
Industrial Vision Systems and Defect Detection
Type
article
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article

Non-contact surface roughness measurement of blasted specimens using machine vision technique

Kyungmok Kim
International Journal of Surface Science and Engineering
Industrial Vision Systems and Defect Detection
article

Non-contact surface roughness measurement of blasted specimens using machine vision technique

Kyungmok Kim
article en

Abstract

This article describes non-contact surface roughness measurement for shot and grit blasted specimens. A simple machine vision algorithm was proposed for determining ten-point mean roughness (Rz) of a specimen after shot and grit blasting. Surfaces cleaned with different blast abrasives were captured by a microscope. Binary images were then created by using Otsu's thresholding method. On the binary image, bright regions were selected, associated with specular reflection of light. The average size of selected regions was calculated in this proposed method. It was found that the average size has a linear relation with ten-point mean roughness of both shot and grit blasted surfaces. It was also identified that the parameter of a linear regression for shot blasting is different from that for grit blasting. On the basis of the relation, it is possible to determine the ten-point mean roughness of a blasted surface with a captured surface image.

International Journal of Surface Science and EngineeringVol. 19(1)
Korea Aerospace University (KR)
Openalex Percentile: Top 72%
Industrial Vision Systems and Defect Detection
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Non-contact surface roughness measurement of blasted specimens using machine vision technique — Kyungmok Kim · International Journal of Surface Science and Engineering (2025) | TGRS Research Map | TGRS