Stack point cloud positioning method based on edge detection and regional growth
A technology of edge detection and region growth, applied in image enhancement, image data processing, instruments, etc., can solve problems such as low segmentation efficiency, easy to be affected by sundries on trucks, difficult to accurately select cluster segmentation distance threshold, etc., to achieve The effect of improving the positioning accuracy of the stack
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[0068] Taking this example as an example, there are three truck stacks to be identified. After point cloud processing, the stack point cloud blocks that meet the normal & volume criterion are c1,...,c6 respectively. Then calculate the average value of the point cloud for each point cloud block (x i ,y i )(i=1,...,6) as the center coordinates of each pallet. The calculated coordinates of the pallets are shown in Table 1:
[0069] Table 1: Coordinates of the center of the pallet
[0070] Stacking piece 1 2 3 4 5 6 x / m 0.486 0.489 0.298 0.296 0.117 0.118 y / m -1.508 -1.484 0.260 0.284 2.510 2.534
[0071] Since the stacks are arranged according to the Y axis in this example, the y coordinates are sorted (the one with the smaller y is the front), and then the midpoint position is calculated in pairs (X j ,Y j ), j=1,2,3. In addition, in this example, the basic parameters of the stack to be identified are shown in Table 2:
[0072] Ta...
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