An Accurate Rigid Body Registration Method Based on Fusion of Point Set Data and Feature Information

Abstract

The invention discloses an accurate rigid body registration method based on the fusion of point set data and feature information. The template point set and the target point set to be registered are known, and the principal component analysis method is used to reduce the dimensionality of the data and extract relatively stable feature information; then a point set registration model based on the fusion of the original point set and feature information is established. For this model, establish the correspondence between the corresponding points between the target point set and the template point set, use the point-to-point correspondence between the template point set and the target point set to solve the transformation parameters of spatial registration, and perform spatial transformation on the target point set ; Iterate the previous step until the mean square error between the corresponding point pairs of the target point set and the template point set is less than a given threshold or reaches the maximum number of iterations, and finally complete the registration of the target point set and the template point set. The invention has higher accuracy and better robustness for data with many noise points and outliers, and the method can be applied to medical image registration, scene reconstruction and positioning.

Description

【Technical field】 [0001] The invention belongs to the technical field of computer vision and image processing, and relates to an accurate rigid body registration method based on fusion of point set data and feature information. 【Background technique】 [0002] In recent years, with the rapid development of medical imaging technology, more and more advanced equipment is used in clinical practice. However, due to differences in equipment and image shooting time, it is impossible to intuitively observe the changes before and after surgery. Therefore, applying registration technology to medical image analysis is conducive to the implementation of precision medicine. Point set registration is a hot issue in the research fields of digital image processing, pattern recognition, computer vision, etc. It can transform images from different sources or at different times through a series of spatial transformations to make their corresponding points consistent in space. [0003] In the ...

AI Technical Summary

Problems solved by technology

However, in actual medical datasets and scene datasets, there are many noise points and outliers in the data.

For data with noise points and outliers, the above method is used for registration, and the registration effect is not very ideal

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