基于RANSAC的激光网格标记图像特征提取

在三维立体视觉中,工件表面的特征提取是三维重构的前提和关键。但是,工件表面的自然特征往往表现得不够明显,使得特征的提取非常困难。因此,经常使用激光网格投影到待检测的工件表面,使工件表面具备确定的可识别特征。针对激光网格标记图像的特点,在随机抽样一致性RANSAC算法的基础上,提出了像素权重化和假设模型预检验的方法,用于激光网格标记的直线特征提取。实验结果表明,该方法不仅克服了RANSAC算法计算量大和参数敏感的缺点,在实际图像的激光网格直线特征提取过程中也具有很好的准确性和鲁棒性。

Laser marking grid image feature extraction based on RANSAC

In 3D vision technology, the feature extraction of the surface of the workpiece is the premise and key of 3D reconstruction. However, the natural features often appear less obvious so the feature extraction is very difficult. The laser grid is often projected onto the surface of the workpiece so that the workpiece surface can be identified with definable characteristics. Aiming at the characteristics of laser grid mark images, we propose a method of pixel weights and hypothetical model pre-detection based on the RANSAC algorithm for line feature extraction. Experimental results show that this method can not only overcome the disadvantages of large computation and parameter sensitivity of the RANSAC algorithm, but also has good accuracy and robustness.