Metal surface quality assessment using 2D texture features

Konstantin Trambitckii, Katharina Anding, Galina Polte, Daniel Garten, Victor Musalimov, Petr Kuritcyn

Abstract

Quality assessment is an important step in production processes of metal parts. This step is required in order to check whether surface quality meets the requirements. Progress in the field of computing technologies and computer vision gives the possibility of surface quality assessment using industrial cameras and image processing methods. Authors of different papers proposed various texture feature algorithms which are suitable for different fields of images processing. In this research 27 texture features were calculated for surface images taken in the different lighting conditions. Correlation coefficients between these 2D texture features and 11 roughness 3D parameters were calculated. A strong correlation between 2D features and 3D parameters occurred for images captured under ring light conditions.

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IMEKO-TC10-2016-059.pdf

DOI

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IMEKO TC

TC10 - Measurement for Diagnostics, Optimization and Control

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