Intelligent Point Cloud Edge Detection Method Based on Projection Transformation | Zendy

Juan Zhu | Zendy; Xiaofeng Yue | Zendy; Jipeng Huang | Zendy; Zongwei Huang | Zendy

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Intelligent Point Cloud Edge Detection Method Based on Projection Transformation

Author(s) -

Juan Zhu,

Xiaofeng Yue,

Jipeng Huang,

Zongwei Huang

Publication year - 2021

Publication title -

wireless communications and mobile computing

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.42

H-Index - 64

eISSN - 1530-8677

pISSN - 1530-8669

DOI - 10.1155/2021/2706462

Subject(s) - computer science , transformation (genetics) , projection (relational algebra) , enhanced data rates for gsm evolution , point cloud , computer vision , cloud computing , artificial intelligence , edge detection , point (geometry) , algorithm , image processing , image (mathematics) , geometry , mathematics , biochemistry , chemistry , gene , operating system

An edge detection method based on projection transformation is proposed. First, the vertical projection transformation is carried out on the target point cloud. Data X and data Y are normalized to the width and height of the image, respectively. Data Z is normalized to the range of 0-255, and the depth represents the gray level of the image. Then, the Canny algorithm is used to detect the edge of the projection transformed image, and the detected edge data is back projected to extract the edge point cloud in the point cloud. Evaluate the performance by calculating the normal vector of the edge point cloud. Compared with the normal vector of the whole data point cloud of the target, the normal vector of the edge point cloud can well express the characteristics of the target, and the calculation time is reduced to 10% of the original.

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