Investigation of Correlation between Image Features of Machined Surface and Surface Roughness

• Main Authors: Ilija Svalina, Sara Havrlišan*, Katica Šimunović, Tomislav Šarić
• Format: Article
• Language: English
• Published: Faculty of Mechanical Engineering in Slavonski Brod, Faculty of Electrical Engineering in Osijek, Faculty of Civil Engineering in Osijek 2020-01-01
• Series: Tehnički Vjesnik
• Subjects: correlation; digital image features of machined surface; face milling; image features ranking; surface roughness
• Online Access: https://hrcak.srce.hr/file/340456

Alternative approach to surface roughness evaluation is mostly based on the analysis of digital images of machined surfaces i.e. on extracting various features from the matrix mathematically representing a digital image. This paper analyses correlation between 23 different digital image features and the surface roughness for two different materials: aluminium and stainless steel. Machined surfaces for both materials were acquired by face milling. Factorial design 6 × 5 × 2 with two replicates was conducted for each material with cutting parameters being varied on various numbers of levels. Based on the correlation coefficients the results showed that the best ranked features regardless of the machined material were the features based on statistic measures.