Track Line Recognition Based on Morphological Thinning Algorithm
In the field of intelligent driving of freight trains, determining the track line ahead of the train is an important function in the autopilot technology of such trains. Combining the characteristics of freight railway tracks, we conduct an in-depth analysis of the shortcomings of object detection t...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-11-01
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| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/12/22/11320 |
| _version_ | 1797466056865873920 |
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| author | Weilong Niu Zan Chen Yihui Zhu Xiaoguang Sun Xuan Li |
| author_facet | Weilong Niu Zan Chen Yihui Zhu Xiaoguang Sun Xuan Li |
| author_sort | Weilong Niu |
| collection | DOAJ |
| description | In the field of intelligent driving of freight trains, determining the track line ahead of the train is an important function in the autopilot technology of such trains. Combining the characteristics of freight railway tracks, we conduct an in-depth analysis of the shortcomings of object detection technology in extracting track lines and propose an improved Zhang–Suen (ZS) thinning theory for a railway track line recognition algorithm. Through image preprocessing and single pixel thinning steps, a continuous track line is obtained and then processed by a denoising algorithm to obtain a complete track line. Experimental results show that the track extracted by our method has good continuity and less noise. It can simultaneously perform track detection on straight roads, curves and turnouts, and is suitable for changing weather conditions such as sunny daytime, mild rainy daytime, cloudy daytime, night with lamp lighting and night without lamp lighting conditions. |
| first_indexed | 2024-03-09T18:30:37Z |
| format | Article |
| id | doaj.art-bcad03be585f474fa94fcbfb6bed639e |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-09T18:30:37Z |
| publishDate | 2022-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-bcad03be585f474fa94fcbfb6bed639e2023-11-24T07:33:26ZengMDPI AGApplied Sciences2076-34172022-11-0112221132010.3390/app122211320Track Line Recognition Based on Morphological Thinning AlgorithmWeilong Niu0Zan Chen1Yihui Zhu2Xiaoguang Sun3Xuan Li4School of Rail Transportation, Soochow University, Suzhou 215137, ChinaSchool of Rail Transportation, Soochow University, Suzhou 215137, ChinaSchool of Automation, Nanjing University of Information Science and Technology, Nanjing 210044, ChinaSchool of Mechanical and Electrical Engineering, Yangzhou University, Yangzhou 225127, ChinaSchool of Mechanical and Electrical Engineering, Soochow University, Suzhou 215137, ChinaIn the field of intelligent driving of freight trains, determining the track line ahead of the train is an important function in the autopilot technology of such trains. Combining the characteristics of freight railway tracks, we conduct an in-depth analysis of the shortcomings of object detection technology in extracting track lines and propose an improved Zhang–Suen (ZS) thinning theory for a railway track line recognition algorithm. Through image preprocessing and single pixel thinning steps, a continuous track line is obtained and then processed by a denoising algorithm to obtain a complete track line. Experimental results show that the track extracted by our method has good continuity and less noise. It can simultaneously perform track detection on straight roads, curves and turnouts, and is suitable for changing weather conditions such as sunny daytime, mild rainy daytime, cloudy daytime, night with lamp lighting and night without lamp lighting conditions.https://www.mdpi.com/2076-3417/12/22/11320track line recognitionobject detectionimproved ZS thinningsingle pixelcontinuity |
| spellingShingle | Weilong Niu Zan Chen Yihui Zhu Xiaoguang Sun Xuan Li Track Line Recognition Based on Morphological Thinning Algorithm Applied Sciences track line recognition object detection improved ZS thinning single pixel continuity |
| title | Track Line Recognition Based on Morphological Thinning Algorithm |
| title_full | Track Line Recognition Based on Morphological Thinning Algorithm |
| title_fullStr | Track Line Recognition Based on Morphological Thinning Algorithm |
| title_full_unstemmed | Track Line Recognition Based on Morphological Thinning Algorithm |
| title_short | Track Line Recognition Based on Morphological Thinning Algorithm |
| title_sort | track line recognition based on morphological thinning algorithm |
| topic | track line recognition object detection improved ZS thinning single pixel continuity |
| url | https://www.mdpi.com/2076-3417/12/22/11320 |
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