基于多视觉特征获取与信息融合的焊道识别方法

焊接过程的复杂性与对象的多样性对焊缝视觉识别与跟踪提出了较高要求,依靠单一特征难以保证识别算法的稳定性与可靠性.文中提出了基于置信度加权的信息融合方法,对获得的不同光照条件下的同视场图像分别进行结构光条形状特征与灰度特征的提取,并分别根据两者的结果进行焊缝边缘的识别,将结果表示为位置的概率密度与置信度的形式,采用置信度加权的方法对概率密度进行叠加,得到融合结果,并针对算例进行了融合算法的验证.结果表明,算法能够实现稳定准确的焊缝边缘识别.

Visual method for weld seam recognition based on multi-feature extraction and information fusion

The complexity of welding process and the diversity of recognition object require high stability and reliability of weld seam recognition and tracking technology. These requirements can hardly be satisfied by recognition through single feature. An information fusion method based on confidence coefficient weighted probability addition is proposed: the shape feature of structured light stripe and the gray-level feature are extracted from weld seam images captured under different illumination situations. The edges of weld seam are recognized based on the two feature values,represented by probability densities of the edge and the confidence coefficients. The information fusion is realized by weighted probability addition of the probability densities. Seam recognition cases are studied to demonstrate the feasibility of the fusion algorithm. The result demonstrates that the algorithm performs well in terms of recognizing the weld seam edges with precision and stability.