EDGE DETECTION PARAMETER OPTIMIZATION BASED ON THE GENETIC ALGORITHM FOR RAIL TRACK DETECTION
One of the most important parameters in an edge detection process is setting up the proper threshold value. However, that parameter can be different for almost each image, especially for infrared (IR) images. Traditional edge detectors cannot set it adaptively, so they are not very robust. This pape...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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University of Niš
2019-11-01
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| Series: | Facta Universitatis. Series: Mechanical Engineering |
| Online Access: | http://casopisi.junis.ni.ac.rs/index.php/FUMechEng/article/view/5192 |
| _version_ | 1818328411155726336 |
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| author | Milan Pavlović Vlastimir Nikolić Miloš Simonović Vladimir Mitrović Ivan Ćirić |
| author_facet | Milan Pavlović Vlastimir Nikolić Miloš Simonović Vladimir Mitrović Ivan Ćirić |
| author_sort | Milan Pavlović |
| collection | DOAJ |
| description | One of the most important parameters in an edge detection process is setting up the proper threshold value. However, that parameter can be different for almost each image, especially for infrared (IR) images. Traditional edge detectors cannot set it adaptively, so they are not very robust. This paper presents optimization of the edge detection parameter, i.e. threshold values for the Canny edge detector, based on the genetic algorithm for rail track detection with respect to minimal value of detection error. First, determination of the optimal high threshold value is performed, and the low threshold value is calculated based on the well-known method. However, detection results were not satisfactory so that, further on, the determination of optimal low and high threshold values is done. Efficiency of the developed method is tested on set of IR images, captured under night-time conditions. The results showed that quality detection is better and the detection error is smaller in the case of determination of both threshold values of the Canny edge detector. |
| first_indexed | 2024-12-13T12:31:44Z |
| format | Article |
| id | doaj.art-c20fcc62cfb7452587ef7950e25c1269 |
| institution | Directory Open Access Journal |
| issn | 0354-2025 2335-0164 |
| language | English |
| last_indexed | 2024-12-13T12:31:44Z |
| publishDate | 2019-11-01 |
| publisher | University of Niš |
| record_format | Article |
| series | Facta Universitatis. Series: Mechanical Engineering |
| spelling | doaj.art-c20fcc62cfb7452587ef7950e25c12692022-12-21T23:46:00ZengUniversity of NišFacta Universitatis. Series: Mechanical Engineering0354-20252335-01642019-11-0117333334410.22190/FUME190426038P2494EDGE DETECTION PARAMETER OPTIMIZATION BASED ON THE GENETIC ALGORITHM FOR RAIL TRACK DETECTIONMilan Pavlović0Vlastimir Nikolić1Miloš Simonović2Vladimir Mitrović3Ivan Ćirić4College of Applied Technical Sciences NišUniversity of Niš, Faculty of Mechanical EngineeringUniversity of Niš, Faculty of Mechanical EngineeringForsteh d.o.oUniversity of Niš, Faculty of Mechanical EngineeringOne of the most important parameters in an edge detection process is setting up the proper threshold value. However, that parameter can be different for almost each image, especially for infrared (IR) images. Traditional edge detectors cannot set it adaptively, so they are not very robust. This paper presents optimization of the edge detection parameter, i.e. threshold values for the Canny edge detector, based on the genetic algorithm for rail track detection with respect to minimal value of detection error. First, determination of the optimal high threshold value is performed, and the low threshold value is calculated based on the well-known method. However, detection results were not satisfactory so that, further on, the determination of optimal low and high threshold values is done. Efficiency of the developed method is tested on set of IR images, captured under night-time conditions. The results showed that quality detection is better and the detection error is smaller in the case of determination of both threshold values of the Canny edge detector.http://casopisi.junis.ni.ac.rs/index.php/FUMechEng/article/view/5192 |
| spellingShingle | Milan Pavlović Vlastimir Nikolić Miloš Simonović Vladimir Mitrović Ivan Ćirić EDGE DETECTION PARAMETER OPTIMIZATION BASED ON THE GENETIC ALGORITHM FOR RAIL TRACK DETECTION Facta Universitatis. Series: Mechanical Engineering |
| title | EDGE DETECTION PARAMETER OPTIMIZATION BASED ON THE GENETIC ALGORITHM FOR RAIL TRACK DETECTION |
| title_full | EDGE DETECTION PARAMETER OPTIMIZATION BASED ON THE GENETIC ALGORITHM FOR RAIL TRACK DETECTION |
| title_fullStr | EDGE DETECTION PARAMETER OPTIMIZATION BASED ON THE GENETIC ALGORITHM FOR RAIL TRACK DETECTION |
| title_full_unstemmed | EDGE DETECTION PARAMETER OPTIMIZATION BASED ON THE GENETIC ALGORITHM FOR RAIL TRACK DETECTION |
| title_short | EDGE DETECTION PARAMETER OPTIMIZATION BASED ON THE GENETIC ALGORITHM FOR RAIL TRACK DETECTION |
| title_sort | edge detection parameter optimization based on the genetic algorithm for rail track detection |
| url | http://casopisi.junis.ni.ac.rs/index.php/FUMechEng/article/view/5192 |
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