Intelligent Point Cloud Edge Detection Method Based on Projection Transformation

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Abstract

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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Zhu, J., Yue, X., Huang, J., & Huang, Z. (2021). Intelligent Point Cloud Edge Detection Method Based on Projection Transformation. Wireless Communications and Mobile Computing, 2021. https://doi.org/10.1155/2021/2706462

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