Intelligent Point Cloud Edge Detection Method Based on Projection Transformation

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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Cut-Edge Detection Method for Rice Harvesting Based on Machine Vision

Agronomy ◽

10.3390/agronomy10040590 ◽

2020 ◽

Vol 10 (4) ◽

pp. 590

Author(s):

Zhenqian Zhang ◽

Ruyue Cao ◽

Cheng Peng ◽

Renjie Liu ◽

Yifan Sun ◽

...

Keyword(s):

Machine Vision ◽

Edge Detection ◽

Detection Method ◽

Region Of Interest ◽

Average Error ◽

Vertical Projection ◽

Cut Edge ◽

Fitting Method ◽

Combine Harvester ◽

Edge Detection Method

A cut-edge detection method based on machine vision was developed for obtaining the navigation path of a combine harvester. First, the Cr component in the YCbCr color model was selected as the grayscale feature factor. Then, by detecting the end of the crop row, judging the target demarcation and getting the feature points, the region of interest (ROI) was automatically gained. Subsequently, the vertical projection was applied to reduce the noise. All the points in the ROI were calculated, and a dividing point was found in each row. The hierarchical clustering method was used to extract the outliers. At last, the polynomial fitting method was used to acquire the straight or curved cut-edge. The results gained from the samples showed that the average error for locating the cut-edge was 2.84 cm. The method was capable of providing support for the automatic navigation of a combine harvester.

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Building Damage Detection Method Based on Normal Vector Computation of Airborne Point Cloud Data

10.1109/icoim52180.2021.9524377 ◽

2021 ◽

Author(s):

Shusong Huang ◽

Yong Zeng ◽

Wei Yi ◽

Weirong Chen ◽

Wenbo Su ◽

...

Keyword(s):

Damage Detection ◽

Point Cloud ◽

Detection Method ◽

Building Damage ◽

Normal Vector ◽

Point Cloud Data ◽

Cloud Data

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Solving the conjugate tooth profile of screw compressor rotors using edge detection method based on Alpha Shape algorithm

Proceedings of the Institution of Mechanical Engineers Part E Journal of Process Mechanical Engineering ◽

10.1177/0954408919862718 ◽

2019 ◽

Vol 233 (6) ◽

pp. 1217-1230

Author(s):

Jian Yang ◽

Fang-Hong Sun ◽

Zheng Lu

Keyword(s):

Edge Detection ◽

Detection Method ◽

Screw Compressor ◽

Male And Female ◽

Cloud Data ◽

Alpha Shape ◽

Rotor Profile ◽

Fast Processing ◽

Edge Detection Method ◽

Rotor Profiles

While designing a screw compressor, the design of the rotor profiles is the most important because rotor profiles essentially determine the overall performance of the screw compressor. In the field of rotor design, the mutual solution of male and female rotors is characterized by shortcomings such as complex and error-prone calculation, and unsolvable interference. In this study, an edge detection method based on the Alpha Shape algorithm was proposed to avoid the complex calculation process in the traditional planar meshing theory and quickly obtain the point cloud data with singularity points removed. The results show that, with relatively high accuracy and fast processing speed, this algorithm can extract comparatively desirable edges so as to obtain data of the female (male) rotor profile based on the conjugate male (female) rotor profile. The analytical method and the experimental method were used to compare the data of the conjugate rotors, verifying the correctness of the design, which efficiently and highly accurately overcame the problems in mutual solution of male and female rotors. This method can also be applied to design similar conjugate products such as gears, worms, and milling cutters.

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