Bin-Picking中无纹理工件的分割

Segmentation of Texture-Less Object for Bin-Picking

为了解决Bin-Picking系统中无纹理工件的分割问题,提出了一种将颜色域和深度域信息融合的分割方法。该方法首先提取颜色域和深度域的边缘特征,然后基于二者的边缘特征,分别通过形态学预处理获取标记图,利用标记图辅助分水岭分割。融合二者的分割信息获得初分割结果,最后通过区域生长法以颜色域分割结果为边界优化分割区域。实验结果表明该算法适用于Bin-Picking视觉检测环节中无纹理目标的分割,对于复杂场景可获得较好的目标潜在位置区域,具有较高的鲁棒性和实时性。

In order to solve the problem of segmentation for texture-less object in Bin-picking system,a novel segmentation algo⁃rithm based on a mixture of the segmentations on the RGB image and depth map is proposed in the paper.Firstly,The algorithm extracts the edges of RGB image and depth map.Then,with the assistance of these two types of edges,the segmentations of the RGB image and the depth image are obtained respectively by the morphological reconstruction watershed approach.Further⁃more,fusing the RGB image and depth map as integrated segmentation.Finally,the integrated segmentation is refined by seed⁃ed region growth in which the RGB segmentation information is treated as growth boundary.The experimental results show that the method have robustness and the real ability for the Bin-picking visual detection,and it can get better potential location re⁃gions for the complicated situations.