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	An Object Segmentation Method based on Image Contour and Local Convexity for 3D Vision Guided Bin-Picking Applications
	Yunlian Song; Shiqian Wu; Juan Zhao; Feifei Gu; Zhan Song
	2018
会议日期	2018
会议地点	马尔代夫
英文摘要	Segmentation of targets from a set of disordered objects is always plays a significant role in the field of computer vision. In this paper, a novel method of object segmentation of scattered parts, of which dense and accurate 3D point cloud can be obtained by visual measurement technology of the structured light, is proposed and confirmed to be valid without training large datasets. The randomly placed parts are almost separated completely after two dimensional image processing and point cloud segmentation using local convex convexity connections. The segmentation results can guide the grabbing work of robot arms in the bin-picking system.
内容类型	会议论文
源URL	[http://ir.siat.ac.cn:8080/handle/172644/13818]
专题	深圳先进技术研究院_集成所
推荐引用方式 GB/T 7714	Yunlian Song,Shiqian Wu,Juan Zhao,et al. An Object Segmentation Method based on Image Contour and Local Convexity for 3D Vision Guided Bin-Picking Applications[C]. 见:. 马尔代夫. 2018.

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