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A New Approach for 3D Edge Extraction by Fusing Point Clouds and Digital Images

机译:定位点云和数字图像的3D边缘提取新方法

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Edges are crucial features for object segmentation and classification in both image and point cloud processing. Though many research efforts have been made in edge extraction and enhancement in both areas, their applications are limited respectively owing to their own technical properties. This paper presents a new approach to integrating the edge pixels in the 2D image into boundary data in the 3D point cloud by establishing the mapping relationship between these two types of data to represent the 3D edge features of the object. The 3D edge extraction - based on the adoption of Microsoft Kinect as a 3D sensor - involves the following three steps: first, the generation of a range image from the point cloud of the object, second the edge extraction in the range image and edge extraction in the digital image, and finally edge data integration by referring to the correspondence map between point cloud data and image pixels.
机译:边缘是图像和点云处理中对象分割和分类的关键特征。虽然在两个领域的边缘提取和增强中已经进行了许多研究努力,但由于其自己的技术性质,它们的应用程序是有限的。本文通过在这两种类型的数据之间建立映射关系来表示将2D图像中的边缘像素集成到3D点云中的边界数据中的新方法来表示对象的3D边缘特征。 3D边缘提取 - 基于通过Microsoft Kinect作为3D传感器 - 涉及以下三个步骤:首先,从对象的点云生成范围图像,在范围图像和边缘提取中的第二边缘提取在数字图像中,最后通过参考点云数据和图像像素之间的对应映射来实现边缘数据集成。

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