结构光视觉焊接接头鲁棒识别

针对具有直线段特征的焊接接头,提出了一种基于模型的识别方法.通过对图像列方向上的光条纹灰度分布质心点序列的计算并利用分段直线段最小二乘拟合提取了结构光条纹中心线的形状特征,进一步利用预先定义的基元符号实现了接头轮廓的定性形状描述,最后实现了基于"假设一检验"的模型匹配方法.在进行匹配时,利用模型的先验信息并结合基元特征融合与特征关系重建规则恢复因飞溅、二次反光以及定位焊点等因素而未被提取到的接头轮廓信息,保证了接头识别的正确性.结果表明,即使在图像中有多种干扰的情况下,通过结合高层模型信息与底层图像处理结果仍可以保证结构光视觉焊接接头识别的鲁棒性.

Robust joint recognition with structured-light vision sensing

A model-based method is proposed for recognition of weld joints composed of line segment features.Shape features of the structured-light stripe centerline are extracted sequentially by calculating the peak mass position of gray distribution for the image columns and fitting the piecewise line segments using the least squares method, then stripe profile is described qualitatively by predefined primitive labels, and lastly a hypothesize-verification based model matching algorithm is implemented to recognize the joint.During the matching, undetected portion of joint profile, due to optical noises such as welding spatters, secondary reflection, tack weld, and other unexpected imaged sources, can be recovered to ensure the correct recognition results by merging profile''s primitives and reconstructing the relations with the top-level heuristic knowledge of the joint models.Experiments show, even in a cluttered environment with different disturbances, correct results can be acquired by combining top-level model and bottom-level data.