Comparison of Correlation between 3D Surface Roughness and Laser Speckle Pattern for Experimental Setup Using He-Ne as Laser Source and Laser Pointer as Laser Source
Correlation between 3D surface roughness and characteristic features extracted from laser speckle pattern was done using an inexpensive laser pointer and a digital single lens reflex (DSLR) camera in previous research work. There had been no comparison work done between the experimental setup which...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-08-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/22/16/6003 |
| _version_ | 1797408046884847616 |
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| author | Suganandha Bharathi Jayabarathi Mani Maran Ratnam |
| author_facet | Suganandha Bharathi Jayabarathi Mani Maran Ratnam |
| author_sort | Suganandha Bharathi Jayabarathi |
| collection | DOAJ |
| description | Correlation between 3D surface roughness and characteristic features extracted from laser speckle pattern was done using an inexpensive laser pointer and a digital single lens reflex (DSLR) camera in previous research work. There had been no comparison work done between the experimental setup which uses a laser pointer, which has a diode laser as the laser source, and the experimental setup, which uses a He-Ne laser as the laser source. As such, in the current work, a comparison study between two experimental setups was carried out. One experimental setup was using a He-Ne laser, spatial filter, and charged coupled device (CCD) camera, while another experimental setup was using a laser pointer and DSLR camera. The laser beam was illuminated at angles of 30°, 45°, and 60° from the horizontal. When a laser beam falls on the surface, the beam gets scattered, and the scattered beam undergoes interference and produces speckle patterns which are captured using a camera. Using a Matlab program, the gray level co-occurrence matrix (GLCM) characteristic features, such as contrast (GLCM), correlation (GLCM), energy (GLCM), entropy (GLCM), homogeneity (GLCM), and maximum probability, and non-GLCM characteristic features, such as mean, standard deviation (STD), uniformity, entropy, normalized R, and white-to-black ratio (W/B), were extracted and correlated with 3D surface roughness parameters. The coefficient of determination (R<sup>2</sup>) was determined for each case. Compared to the setup using a laser pointer, the setup using a He-Ne laser gave better results. In the setup using the He-Ne laser, there were correlations with a coefficient of determination R<sup>2</sup> ≥ 0.7 at illumination angles of 30°, 45°, and 60°, whereas in the setup using a laser pointer, there were correlations with R<sup>2</sup> ≥ 0.7 at illumination angles of 30° and 45°. Mean characteristic features had more correlations with R<sup>2</sup> ≥ 0.7 in the case of the angle of illumination of 45° (7 out of 36 correlations) and 60° (11 out of 82 correlations), while R-normalized characteristic features had more correlations with R<sup>2</sup> ≥ 0.7 in the case of the angle of illumination of 30° (9 out of 38 correlations) for the setup using the He-Ne laser. Correlation (GLCM) had more correlations with R<sup>2</sup> ≥ 0.7 in the case of the setup using a laser pointer (2 out of 2 correlations for illumination angle of 30°, and 4 out of 19 correlations for an illumination angle of 45°). Roughness parameters <i>S<sub>a</sub></i> and <i>S<sub>q</sub></i> had more correlations with R<sup>2</sup> ≥ 0.7 for an illumination angle of 30° (1 out of 2 correlations each), and <i>S<sub>p</sub></i> and <i>S<sub>z</sub></i> had more correlations with R<sup>2</sup> ≥ 0.7 for an illumination angle of 45° (4 out of 19 correlations each) in the case of the setup using a laser pointer. The novelty of this work is (1) being a correlation study between 3D surface roughness and speckle pattern using a He-Ne laser and spatial filter, and (2) being a comparison study between two experimental setups on the correlation between 3D surface roughness and speckle pattern. |
| first_indexed | 2024-03-09T03:52:39Z |
| format | Article |
| id | doaj.art-9e4b5f552d05475ca2d3262bbeaeffe3 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-09T03:52:39Z |
| publishDate | 2022-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-9e4b5f552d05475ca2d3262bbeaeffe32023-12-03T14:25:39ZengMDPI AGSensors1424-82202022-08-012216600310.3390/s22166003Comparison of Correlation between 3D Surface Roughness and Laser Speckle Pattern for Experimental Setup Using He-Ne as Laser Source and Laser Pointer as Laser SourceSuganandha Bharathi Jayabarathi0Mani Maran Ratnam1Faculty of Engineering and Computer Technology, AIMST University, Semeling, Bedong 08100, Kedah, MalaysiaSchool of Mechanical Engineering, Engineering Campus, Universiti Sains Malaysia, Nibong Tebal 14300, Penang, MalaysiaCorrelation between 3D surface roughness and characteristic features extracted from laser speckle pattern was done using an inexpensive laser pointer and a digital single lens reflex (DSLR) camera in previous research work. There had been no comparison work done between the experimental setup which uses a laser pointer, which has a diode laser as the laser source, and the experimental setup, which uses a He-Ne laser as the laser source. As such, in the current work, a comparison study between two experimental setups was carried out. One experimental setup was using a He-Ne laser, spatial filter, and charged coupled device (CCD) camera, while another experimental setup was using a laser pointer and DSLR camera. The laser beam was illuminated at angles of 30°, 45°, and 60° from the horizontal. When a laser beam falls on the surface, the beam gets scattered, and the scattered beam undergoes interference and produces speckle patterns which are captured using a camera. Using a Matlab program, the gray level co-occurrence matrix (GLCM) characteristic features, such as contrast (GLCM), correlation (GLCM), energy (GLCM), entropy (GLCM), homogeneity (GLCM), and maximum probability, and non-GLCM characteristic features, such as mean, standard deviation (STD), uniformity, entropy, normalized R, and white-to-black ratio (W/B), were extracted and correlated with 3D surface roughness parameters. The coefficient of determination (R<sup>2</sup>) was determined for each case. Compared to the setup using a laser pointer, the setup using a He-Ne laser gave better results. In the setup using the He-Ne laser, there were correlations with a coefficient of determination R<sup>2</sup> ≥ 0.7 at illumination angles of 30°, 45°, and 60°, whereas in the setup using a laser pointer, there were correlations with R<sup>2</sup> ≥ 0.7 at illumination angles of 30° and 45°. Mean characteristic features had more correlations with R<sup>2</sup> ≥ 0.7 in the case of the angle of illumination of 45° (7 out of 36 correlations) and 60° (11 out of 82 correlations), while R-normalized characteristic features had more correlations with R<sup>2</sup> ≥ 0.7 in the case of the angle of illumination of 30° (9 out of 38 correlations) for the setup using the He-Ne laser. Correlation (GLCM) had more correlations with R<sup>2</sup> ≥ 0.7 in the case of the setup using a laser pointer (2 out of 2 correlations for illumination angle of 30°, and 4 out of 19 correlations for an illumination angle of 45°). Roughness parameters <i>S<sub>a</sub></i> and <i>S<sub>q</sub></i> had more correlations with R<sup>2</sup> ≥ 0.7 for an illumination angle of 30° (1 out of 2 correlations each), and <i>S<sub>p</sub></i> and <i>S<sub>z</sub></i> had more correlations with R<sup>2</sup> ≥ 0.7 for an illumination angle of 45° (4 out of 19 correlations each) in the case of the setup using a laser pointer. The novelty of this work is (1) being a correlation study between 3D surface roughness and speckle pattern using a He-Ne laser and spatial filter, and (2) being a comparison study between two experimental setups on the correlation between 3D surface roughness and speckle pattern.https://www.mdpi.com/1424-8220/22/16/6003surface roughnessspeckle patternmilled surfacenon-contactoptical technique |
| spellingShingle | Suganandha Bharathi Jayabarathi Mani Maran Ratnam Comparison of Correlation between 3D Surface Roughness and Laser Speckle Pattern for Experimental Setup Using He-Ne as Laser Source and Laser Pointer as Laser Source Sensors surface roughness speckle pattern milled surface non-contact optical technique |
| title | Comparison of Correlation between 3D Surface Roughness and Laser Speckle Pattern for Experimental Setup Using He-Ne as Laser Source and Laser Pointer as Laser Source |
| title_full | Comparison of Correlation between 3D Surface Roughness and Laser Speckle Pattern for Experimental Setup Using He-Ne as Laser Source and Laser Pointer as Laser Source |
| title_fullStr | Comparison of Correlation between 3D Surface Roughness and Laser Speckle Pattern for Experimental Setup Using He-Ne as Laser Source and Laser Pointer as Laser Source |
| title_full_unstemmed | Comparison of Correlation between 3D Surface Roughness and Laser Speckle Pattern for Experimental Setup Using He-Ne as Laser Source and Laser Pointer as Laser Source |
| title_short | Comparison of Correlation between 3D Surface Roughness and Laser Speckle Pattern for Experimental Setup Using He-Ne as Laser Source and Laser Pointer as Laser Source |
| title_sort | comparison of correlation between 3d surface roughness and laser speckle pattern for experimental setup using he ne as laser source and laser pointer as laser source |
| topic | surface roughness speckle pattern milled surface non-contact optical technique |
| url | https://www.mdpi.com/1424-8220/22/16/6003 |
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