Investigation of Correlation between Image Features of Machined Surface and Surface Roughness
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...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Faculty of Mechanical Engineering in Slavonski Brod, Faculty of Electrical Engineering in Osijek, Faculty of Civil Engineering in Osijek
2020-01-01
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| Series: | Tehnički Vjesnik |
| Subjects: | |
| Online Access: | https://hrcak.srce.hr/file/340456 |
| _version_ | 1797207310558298112 |
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| author | Ilija Svalina Sara Havrlišan* Katica Šimunović Tomislav Šarić |
| author_facet | Ilija Svalina Sara Havrlišan* Katica Šimunović Tomislav Šarić |
| author_sort | Ilija Svalina |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-24T09:20:53Z |
| format | Article |
| id | doaj.art-e747176f078b4acf8721cfd69127e2b5 |
| institution | Directory Open Access Journal |
| issn | 1330-3651 1848-6339 |
| language | English |
| last_indexed | 2024-04-24T09:20:53Z |
| publishDate | 2020-01-01 |
| publisher | Faculty of Mechanical Engineering in Slavonski Brod, Faculty of Electrical Engineering in Osijek, Faculty of Civil Engineering in Osijek |
| record_format | Article |
| series | Tehnički Vjesnik |
| spelling | doaj.art-e747176f078b4acf8721cfd69127e2b52024-04-15T16:03:25ZengFaculty of Mechanical Engineering in Slavonski Brod, Faculty of Electrical Engineering in Osijek, Faculty of Civil Engineering in OsijekTehnički Vjesnik1330-36511848-63392020-01-01271273610.17559/TV-20191212122953Investigation of Correlation between Image Features of Machined Surface and Surface RoughnessIlija Svalina0Sara Havrlišan*1Katica Šimunović2Tomislav Šarić3Mechanical Engineering Faculty in Slavonski Brod, Josip Juraj Strossmayer University of Osijek, Trg I. Brlić Mažuranić 2, HR-35000 Slavonski Brod, CroatiaMechanical Engineering Faculty in Slavonski Brod, Josip Juraj Strossmayer University of Osijek, Trg I. Brlić Mažuranić 2, HR-35000 Slavonski Brod, CroatiaMechanical Engineering Faculty in Slavonski Brod, Josip Juraj Strossmayer University of Osijek, Trg I. Brlić Mažuranić 2, HR-35000 Slavonski Brod, CroatiaMechanical Engineering Faculty in Slavonski Brod, Josip Juraj Strossmayer University of Osijek, Trg I. Brlić Mažuranić 2, HR-35000 Slavonski Brod, CroatiaAlternative 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.https://hrcak.srce.hr/file/340456correlationdigital image features of machined surfaceface millingimage features rankingsurface roughness |
| spellingShingle | Ilija Svalina Sara Havrlišan* Katica Šimunović Tomislav Šarić Investigation of Correlation between Image Features of Machined Surface and Surface Roughness Tehnički Vjesnik correlation digital image features of machined surface face milling image features ranking surface roughness |
| title | Investigation of Correlation between Image Features of Machined Surface and Surface Roughness |
| title_full | Investigation of Correlation between Image Features of Machined Surface and Surface Roughness |
| title_fullStr | Investigation of Correlation between Image Features of Machined Surface and Surface Roughness |
| title_full_unstemmed | Investigation of Correlation between Image Features of Machined Surface and Surface Roughness |
| title_short | Investigation of Correlation between Image Features of Machined Surface and Surface Roughness |
| title_sort | investigation of correlation between image features of machined surface and surface roughness |
| topic | correlation digital image features of machined surface face milling image features ranking surface roughness |
| url | https://hrcak.srce.hr/file/340456 |
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