Real-Time Seam Extraction Using Laser Vision Sensing: Hybrid Approach with Dynamic ROI and Optimized RANSAC
Laser vision sensors for weld seam extraction face critical challenges due to arc light and spatter interference in welding environments. This paper presents a real-time weld seam extraction method. The proposed framework enhances robustness through the sequential processing of historical frame data...
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MDPI AG
2025-05-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/25/11/3268 |
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| author | Guojun Chen Yanduo Zhang Yuming Ai Baocheng Yu Wenxia Xu |
| author_facet | Guojun Chen Yanduo Zhang Yuming Ai Baocheng Yu Wenxia Xu |
| author_sort | Guojun Chen |
| collection | DOAJ |
| description | Laser vision sensors for weld seam extraction face critical challenges due to arc light and spatter interference in welding environments. This paper presents a real-time weld seam extraction method. The proposed framework enhances robustness through the sequential processing of historical frame data. First, an initial noise-free laser stripe image of the weld seam is acquired prior to arc ignition, from which the laser stripe region and slope characteristics are extracted. Subsequently, during welding, a dynamic region of interest (ROI) is generated for the current frame based on the preceding frame, effectively suppressing spatter and arc interference. Within the ROI, adaptive Otsu thresholding segmentation and morphological filtering are applied to isolate the laser stripe. An optimized RANSAC algorithm, incorporating slope constraints derived from historical frames, is then employed to achieve robust laser stripe fitting. The geometric center coordinates of the weld seam are derived through the rigorous analysis of the optimized laser stripe profile. Experimental results from various types of weld seam extraction validated the accuracy and real-time performance of the proposed method. |
| format | Article |
| id | doaj-art-7e8fa1d45ae04e1fb1d32777407e352a |
| institution | DOAJ |
| issn | 1424-8220 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj-art-7e8fa1d45ae04e1fb1d32777407e352a2025-08-20T03:11:32ZengMDPI AGSensors1424-82202025-05-012511326810.3390/s25113268Real-Time Seam Extraction Using Laser Vision Sensing: Hybrid Approach with Dynamic ROI and Optimized RANSACGuojun Chen0Yanduo Zhang1Yuming Ai2Baocheng Yu3Wenxia Xu4School of Computer Science and Engineering, Wuhan Institute of Technology, Wuhan 430205, ChinaSchool of Computer Science and Engineering, Wuhan Institute of Technology, Wuhan 430205, ChinaSchool of Computer Science and Engineering, Wuhan Institute of Technology, Wuhan 430205, ChinaSchool of Computer Science and Engineering, Wuhan Institute of Technology, Wuhan 430205, ChinaSchool of Computer Science and Engineering, Wuhan Institute of Technology, Wuhan 430205, ChinaLaser vision sensors for weld seam extraction face critical challenges due to arc light and spatter interference in welding environments. This paper presents a real-time weld seam extraction method. The proposed framework enhances robustness through the sequential processing of historical frame data. First, an initial noise-free laser stripe image of the weld seam is acquired prior to arc ignition, from which the laser stripe region and slope characteristics are extracted. Subsequently, during welding, a dynamic region of interest (ROI) is generated for the current frame based on the preceding frame, effectively suppressing spatter and arc interference. Within the ROI, adaptive Otsu thresholding segmentation and morphological filtering are applied to isolate the laser stripe. An optimized RANSAC algorithm, incorporating slope constraints derived from historical frames, is then employed to achieve robust laser stripe fitting. The geometric center coordinates of the weld seam are derived through the rigorous analysis of the optimized laser stripe profile. Experimental results from various types of weld seam extraction validated the accuracy and real-time performance of the proposed method.https://www.mdpi.com/1424-8220/25/11/3268laser visiondynamic ROIoptimized RANSACweld seam extraction |
| spellingShingle | Guojun Chen Yanduo Zhang Yuming Ai Baocheng Yu Wenxia Xu Real-Time Seam Extraction Using Laser Vision Sensing: Hybrid Approach with Dynamic ROI and Optimized RANSAC Sensors laser vision dynamic ROI optimized RANSAC weld seam extraction |
| title | Real-Time Seam Extraction Using Laser Vision Sensing: Hybrid Approach with Dynamic ROI and Optimized RANSAC |
| title_full | Real-Time Seam Extraction Using Laser Vision Sensing: Hybrid Approach with Dynamic ROI and Optimized RANSAC |
| title_fullStr | Real-Time Seam Extraction Using Laser Vision Sensing: Hybrid Approach with Dynamic ROI and Optimized RANSAC |
| title_full_unstemmed | Real-Time Seam Extraction Using Laser Vision Sensing: Hybrid Approach with Dynamic ROI and Optimized RANSAC |
| title_short | Real-Time Seam Extraction Using Laser Vision Sensing: Hybrid Approach with Dynamic ROI and Optimized RANSAC |
| title_sort | real time seam extraction using laser vision sensing hybrid approach with dynamic roi and optimized ransac |
| topic | laser vision dynamic ROI optimized RANSAC weld seam extraction |
| url | https://www.mdpi.com/1424-8220/25/11/3268 |
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