Three-dimensional image registration method based on reselection point strategy and artificial bee colony optimization

Abstract

The invention discloses a three-dimensional image registration method based on a reselection point strategy and an artificial bee colony optimization, which comprises the following steps: (1) samplinga dynamic point cloud to obtain a sampling point set; (2) generating a certain number of bee colonies and initializing the position of the individual bee colonies; (3) determining the Euclidean transformation moment of each honeybee, and transforming the position of the sampling point set according to the Euclidean transformation matrix; 3) transform that sample point set by the Euclidean transform moments and calculate the objective function value; (5) comparing the variation of the optimal objective function value, and if the variation is smaller than the threshold value for successive times, reselecting the point operation to obtain a new sample point set, otherwise, entering the step (6); 6) if that maximum evolutionary algebra is reach, entering the step 7), otherwise return to the step 3); (7) obtaining the optimal Euclidean transformation moment from the optimal solution of the population; And moving the dynamic point cloud to complete image registration. In this method, the re-selection strategy is introduced into the sampling process and the bee-colony algorithm is combined to effectively reduce the time of image registration and improve the performance.

Description

technical field [0001] The invention relates to the technical field of three-dimensional image registration, in particular to a method for three-dimensional image registration based on reselection point strategy and artificial bee colony optimization. Background technique [0002] Three-dimensional imaging refers to the process of collecting depth image data of three-dimensional objects from different angles of view by multiple sensors and forming a complete three-dimensional shape of the measured object. 3D image registration (IR) is a key technology in the field of 3D imaging. Its task is to find the optimal transformation of 3D space, unify multiple depth images collected by multiple sensors into the same coordinate system, and finally restore a complete 3D object. . [0003] At present, in order to improve the speed and accuracy of 3D image registration, the registration method combined with bionic intelligent optimization algorithm has become a research hotspot at home...

AI Technical Summary

Problems solved by technology

[0004] However, many improvement strategies increase the computational complexity while improving the global convergence ability and solution accuracy of the registration algorithm, which affects the actual engineering application effect of the algorithm and reduces the registration completion time.

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