Plant identification and classification method based on three-dimensional point cloud contour fractal dimension value
A three-dimensional point cloud, recognition and classification technology, applied in character and pattern recognition, instruments, computer parts and other directions, can solve the problems of professional level influence, a large number of manual participation, etc., to achieve less errors, classification speed block, intelligent degree high effect
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Embodiment 1
[0087] Embodiment 1 uses the three-dimensional crown point cloud data of four camphor trees with leaves to calculate its fractal value according to the above process, and the fractal value fluctuates around 2.65, wherein the initial side length of the cube is set to 0.01, when the side length of the cube is very small , the corresponding points will deviate from the final fitting straight line result, and the camphor tree points with fewer point clouds will be farther away from the fitting straight line. The slope of the fitted line by the least squares method deflects clockwise, causing the slope of the fitted line to be smaller than when there is no such deviation point in the point set of the log-log coordinate map. The number of point clouds affects the sensitivity of the line fitting deviation to the division scale of the cubic box.
[0088] 2. Cubic box division scale parameter setting
Embodiment 2
[0091] In Example 2, the fractal dimension values of the four camphor trees with leaves calculated by the least square method increase with the increase of the initial side length of the cube box, but the number of points in the corresponding logarithmic coordinate map point set is decreasing , resulting in fewer samples of the least squares method fitting the straight line, and a smaller number of point clouds will make the corresponding fractal dimension value more sensitive to the initial side length of the cube.
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