Surface Roughness Measurement Using Light Sectioning Method and Computer Vision Techniques.
Elhamshary, N., Abouelatta, O., Amar, I., Gadelmawla, E. (2020). Surface Roughness Measurement Using Light Sectioning Method and Computer Vision Techniques.. EKB Journal Management System, 29(1), 13-24. doi: 10.21608/bfemu.2020.132820
N. Elhamshary; Ossama Badie Shafik Abouelatta; Ibrahim Mohamed Ibrahim Elewa Amar; Elamir Samy Gadelmawla. "Surface Roughness Measurement Using Light Sectioning Method and Computer Vision Techniques.". EKB Journal Management System, 29, 1, 2020, 13-24. doi: 10.21608/bfemu.2020.132820
Elhamshary, N., Abouelatta, O., Amar, I., Gadelmawla, E. (2020). 'Surface Roughness Measurement Using Light Sectioning Method and Computer Vision Techniques.', EKB Journal Management System, 29(1), pp. 13-24. doi: 10.21608/bfemu.2020.132820
Elhamshary, N., Abouelatta, O., Amar, I., Gadelmawla, E. Surface Roughness Measurement Using Light Sectioning Method and Computer Vision Techniques.. EKB Journal Management System, 2020; 29(1): 13-24. doi: 10.21608/bfemu.2020.132820

Surface Roughness Measurement Using Light Sectioning Method and Computer Vision Techniques.

MEJ- Mansoura Engineering Journal
Article 20, Volume 29, Issue 1, March 2004, Page 13-24  XML PDF (517.66 K)
Document Type: Research Studies
DOI: 10.21608/bfemu.2020.132820
View on SCiNiTO View on SCiNiTO
Authors
N. Elhamshary1; Ossama Badie Shafik Abouelatta2; Ibrahim Mohamed Ibrahim Elewa Amar* 3; Elamir Samy Gadelmawla4
1Workers University, Mansoura, Egypt
2Production Engineering and Mechanical Design Department,El- Mansoura University, Faculty of Engineering, Mansoura, Egypt
3Production Engineering and Mechanical Design Department., El- Mansoura University, Faculty of Engineering, Mansoura, Egypt
4Production Engineering and Mechanical Design Department, Faculty of Engineering, Mansoura University, 35516 Mansoura, Egypt
Abstract
 The development of new industries has led to a requirement for super-smooth surfaces and for the ability to measure surfaces of industrial parts accurately; therefore, the measurement of engineering surface roughness is becoming increasingly important. In this work, a new approach is introduced to measure surface roughness by combining a light sectioning microscope and a computer vision system. This method has the advantage of being non-contact. The light sectioning microscope is used to view roughness profiles of the specimens to be measured and the vision system is used to capture images for the viewed profiles. A special program (named SRLSVision) has been totally developed in-house using MatlabTM software to analyze the captured images through two modules. The first module is used to extract the roughness profiles from the captured images by applying various image processing and computer vision algorithms. The second module is used to calculate the ISO roughness parameters (22 parameters) from the extracted profiles. The system has been calibrated for metric units and verified using a standard specimen. In addition, the system was used to measure various samples: machined by different operations and the obtained results were compared with the results obtained by measuring the same samples using a stylus instrument. The accuracy of the system proved to be within ±5.5% compared with the stylus instrument readings.
Statistics
Article View: 205
PDF Download: 278