基于激光视觉的角焊缝图像特征点提取
Image feature extraction of fillet weld based on laser vision
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摘要: 提出一种借助线激光从图像中提取角焊缝特征点的方法,克服了线激光在角焊缝表面的反光对提取光条中心线的影响,有效地识别出了角焊缝特征点. 首先,根据局部对比度区分实际光条与反光条纹,用阈值分割结合图像形态学方法分割出实际光条,并确定ROI区域;其次,根据光条截面的灰度分布提取光条中心点;最后,用迭代最小二乘法拟合分段光条中心线方程并确定角焊缝特征点. 结果表明,该方法能够快速准确地提取表面光亮角焊缝的亚像素图像特征点,在主频3.4 GHz的PC机上共用时0.35 s,能够满足焊接速度为0~25 mm/s的普通焊接设备的实时性要求.Abstract: An approach is put forward to extract image feature points of fillet weld with the assistance of laser line. It overcomes the influence of the reflective stripes in the surface of fillet weld and identifies the feature points effectively. Firstly, the actual stripes and reflective stripes were distinguished by local contrast, then the actual stripes were divided by combination of morphological method and threshold segmentation, and the region of interest was determined. Secondly, the center points in light stripes were extracted according to the intensity distribution of the cross-section of light stripe. Finally, the iterative least-squares fitting method was applied to fit the piecewise centerline equations and to determine the fillet feature points. The experimental results show that this method can extract the sub-pixel image feature points from fillet weld with bright surface rapidly and accurately. It costs about 0.35s running on a PC whose CPU is clocked at 3.4 GHz, which can meet the real-time requirements of ordinary welding equipment with welding speed of 0-25 mm/s.
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