Simulation of 3D Image Reconstruction in Rigid body Motion

Huihong Chen,Shiming Li,Yansong Wang

doi:10.1051/matecconf/201823202002

Abstract

3D image reconstruction under rigid body motion is affected by rigid body motion and visual displacement factors, which leads to low quality of 3D image reconstruction and more noise, in order to improve the quality of 3D image reconstruction of rigid body motion. A 3D image reconstruction technique is proposed based on corner detection and edge contour feature extraction in this paper. Region scanning and point scanning are combined to scan rigid body moving object image. The wavelet denoising method is used to reduce the noise of the 3D image. The edge contour feature of the image is extracted. The sparse edge pixel fusion method is used to decompose the feature of the 3D image under the rigid body motion. The irregular triangulation method is used to extract and reconstruct the information features of the rigid body 3D images. The reconstructed feature points are accurately calibrated with the corner detection method to realize the effective reconstruction of the 3D images. The simulation results show that the method has good quality, high SNR of output image and high registration rate of feature points of image reconstruction, and proposed method has good performance of 3D image reconstruction.

Highlights

In order to solve the above problems, we propose a 3D image reconstruction technique based on corner detection and edge contour feature extraction
In order to realize 3D image reconstruction under rigid body motion, we use the region scanning and point scanning technology to scan the image of rigid body moving object, and realize the global spatial scanning of reconstructed object
We propose a 3D image reconstruction technology based on corner detection and edge contour feature extraction

Summary

Introduction

The 3D image reconstruction under rigid body motion is carried out with the method of deformation displacement vector compensation. The disadvantage of this method is that the statistical information expression ability of reconstructed image is poor and the image is greatly affected by noise. In order to solve the above problems, we propose a 3D image reconstruction technique based on corner detection and edge contour feature extraction. The irregular triangulation method is used to extract and reconstruct the information features of the rigid body 3D images. The performance tests are carried out through simulation experiments, which demonstrate the superior performance of the proposed method in improving the performance of 3D image reconstruction under rigid body motion

Image scanning of moving objects of rigid bodies

Simulation test and result analysis

Findings

Conclusions