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Denoising and simplifying method of point cloud model

A point cloud model and model technology, applied in image enhancement, image analysis, instruments, etc., can solve the problems of large memory occupation and long processing time affecting computer operation.

Inactive Publication Date: 2017-06-13
XI'AN POLYTECHNIC UNIVERSITY
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Problems solved by technology

[0003] The purpose of the present invention is to provide a method for denoising and simplifying the point cloud model, which solves the problem that the existing technology takes up a lot of memory, and the processing time is long and affects the operation of the computer.

Method used

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  • Denoising and simplifying method of point cloud model
  • Denoising and simplifying method of point cloud model
  • Denoising and simplifying method of point cloud model

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Embodiment Construction

[0095] The present invention will be described in detail below in conjunction with specific embodiments.

[0096] A method for denoising and simplifying a point cloud model of the present invention, such as figure 1 As shown, the specific steps are as follows:

[0097] Step 1, collect the image and preprocess the image, specifically,

[0098] Step 1.1, acquire the original 3D point cloud model image through the kinect vision sensor,

[0099] In step 1.2, preprocessing the 3D point cloud model image acquired in step 1.1, performing segmentation and extraction using a straight-through filter method, to obtain a 3D point cloud model image.

[0100] Step 2: Remove large-scale noise from the 3D point cloud model picture obtained in step 1. The specific implementation method is as follows:

[0101] Step 2.1: Use statistical filtering to remove some large-scale noise points. For each data point q in the 3D point cloud model n , assuming q n The distance to any point is d i ,q ...

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Abstract

The invention discloses a denoising and simplifying method of a point cloud model. The method specifically comprises the first step of collecting an image and preprocessing the image; the second step of conducting removal of large-scale noise on a three-dimensional point cloud model obtained in the first step; the third step of adopting moving least square to remove small-scale noise; the fourth step of conducting grid downsampling based on voxel on point cloud data which is denoised in the third step to obtain a simplified point cloud model. The problem in the prior art that the occupied memory is large, and the operation of a computer is influenced due to long processing time is solved.

Description

technical field [0001] The invention belongs to the technical field of three-dimensional point cloud reconstruction, and in particular relates to a method for denoising and simplifying a point cloud model. Background technique [0002] Due to random factors such as human beings or the defects of the scanning equipment itself, as well as the diversity of point cloud model features and the complexity of the noise itself, the acquired data is inevitably noisy, and the existence of noise seriously affects the accuracy of subsequent modeling and correlation. processing efficiency. At the same time, with the continuous improvement of the accuracy of 3D data scanning equipment and the wide application of point cloud data in large-scale complex scene modeling, the collected point cloud data is often too dense, and we reconstruct a complete point cloud product. It is necessary to merge multiple pieces of point cloud data from different angles, resulting in a huge amount of data. If ...

Claims

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Application Information

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IPC IPC(8): G06T5/00
CPCG06T2207/10028G06T5/70
Inventor 李仁忠杨曼张缓缓刘阳阳
Owner XI'AN POLYTECHNIC UNIVERSITY
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