A laser radar point cloud power line classification method based on normal random sampling distribution

A random sampling, lidar technology, applied in the field of data processing, to achieve the effect of improving classification efficiency

A random sampling, lidar technology, applied in the field of data processing, to achieve the effect of improving classification efficiency

CN109948682AActive Publication Date: 2019-06-28HUNAN UNIV OF SCI & TECH
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  • A laser radar point cloud power line classification method based on normal random sampling distribution
  • A laser radar point cloud power line classification method based on normal random sampling distribution
  • A laser radar point cloud power line classification method based on normal random sampling distribution

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Embodiment Construction

[0047] The present invention will be further described below in conjunction with the drawings and embodiments.

[0048] Such as figure 1 As shown, a lidar point cloud power line classification method based on normal random sampling distribution includes the following steps:

[0049] (1) Preprocess the original point cloud data, establish a digital terrain model, and use elevation filtering to extract power line candidate points. The specific steps of step (1) are:

[0050] 1-1) Based on the original point cloud data, the conventional and traditional filtering mechanism of significant non-power line points (noise points, missed points, etc.), point cloud data preprocessing;

[0051] 1-2) Describe the scene according to the quality of the original point cloud data, and design a ground seed point spacing of 0.5 meters;

[0052] 1-3) Process the point cloud data into blocks to obtain several small areas, and select a ground seed point in each small area;

[0053] 1-4) Use the obtained seed ...

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Abstract

The invention discloses a laser radar point cloud power line classification method based on normal random sampling distribution, and the method comprises the following steps: (1) carrying out the preprocessing of original point cloud data, building a digital terrain model, and carrying out the rough extraction of power line candidate points through employing elevation filtering; (2) for the roughly extracted power line candidate point data, further optimizing and extracting power line candidate points in a three-dimensional space based on a normal distribution transformation algorithm; and (3)aiming at the optimized and extracted power line candidate point data, realizing accurate extraction of the power line points in a two-dimensional space by adopting a random sampling consistency algorithm principle. With the method of the invention adopted, power line classification can be realized in laser radar point cloud data of various complex environments such as an urban forest region; andan accurate power line extraction result is provided, so that the point cloud data classification efficiency is greatly improved, a new idea is provided for classification of various point cloud data, and accurate and comprehensive analysis data is provided for work such as power line inspection and the like.

Description

Technical field [0001] The present invention relates to the technical field of data processing, in particular to a method for classifying power lines of lidar point clouds based on normal random sampling distribution. Background technique [0002] As a novel and efficient space detection method, lidar technology can quickly acquire a large number of point cloud data of the target scene with precise three-dimensional space coordinates in a short time, but compared with the progress made in the hardware performance and indicators of the lidar system The software processing of lidar point cloud data is still in its infancy. Facing the massive point cloud data acquired by the lidar hardware system, how to effectively use it is a major issue facing the current lidar point cloud data processing field. problem. At the same time, with the rapid development of my country's economy in various fields, the demand for electricity in all walks of life has grown very rapidly. In the face of l...

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Application Information

Patent Timeline
28 Jun 2019
Publication
CN109948682A
IPC
G06K9/62; G06T17/00; G06F17/50
Inventors
王艳军