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Weld Line Detection and Tracking via Spatial-Temporal Cascaded Hidden Markov Models and Cross Structured Light

机译:通过时空级联隐马尔可夫模型和交叉结构光进行焊缝检测和跟踪

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摘要

Unlike weld seam detection in a welding process, weld line localization for inspection is usually performed outdoors and challenged by noise and variation of illumination intensity. In this paper, we propose a weld line localization approach for mobile platform via a cross structured light (CSL) device and spatial-temporal cascaded hidden Markov models (HMMs). A CSL device is designed to project cross red laser stripes on weldment surfaces and capture the weld convexity in video sequences. Stripe edge images are extracted and then a spatial HMM is designed to detect the regions of interest (ROIs) in the video frames. Detected ROIs in successive video frames are fed to the proposed temporal HMM as observations to track the weld lines. In this way, we incorporate both the spatial characteristics of laser stripes and the continuity of the weld lines in an optimal framework. Experiments show that the proposed approach can effectively reduce the influence of illumination and noise, contributing a robust weld line detection and tracking system.
机译:与焊接过程中的焊缝检测不同,用于检查的焊缝线定位通常在户外进行,并且受到噪声和照明强度变化的挑战。在本文中,我们通过交叉结构光(CSL)设备和时空级联隐马尔可夫模型(HMM),提出了一种用于移动平台的焊缝定位方法。 CSL设备设计用于在焊接件表面投射红色十字形激光条纹,并捕获视频序列中的焊接凸度。提取条纹边缘图像,然后设计空间HMM以检测视频帧中的关注区域(ROI)。在连续视频帧中检测到的ROI被馈送到建议的时间HMM作为观察以跟踪焊缝。通过这种方式,我们将激光条纹的空间特征和焊缝的连续性都整合到了最佳框架中。实验表明,该方法可以有效减少照明和噪声的影响,为焊接线的检测和跟踪系统提供了强大的支持。

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