Evolutionary Optimisation Methods for Template Based Image Registration

TL;DR

This paper compares evolutionary algorithms and Nelder-Mead Simplex for template-based image registration, analyzing their precision, accuracy, and potential improvements in performance.

Contribution

It provides a comparative analysis of multiple optimization techniques for image registration and suggests directions for enhancing their efficiency.

Findings

SA is the most precise method

GA is the most accurate method

PSO offers a good balance of precision and accuracy

Abstract

This paper investigates the use of evolutionary optimisation techniques to register a template with a scene image. An error function is created to measure the correspondence of the template to the image. The problem presented here is to optimise the horizontal, vertical and scaling parameters that register the template with the scene. The Genetic Algorithm, Simulated Annealing and Particle Swarm Optimisations are compared to a Nelder-Mead Simplex optimisation with starting points chosen in a pre-processing stage. The paper investigates the precision and accuracy of each method and shows that all four methods perform favourably for image registration. SA is the most precise, GA is the most accurate. PSO is a good mix of both and the Simplex method returns local minima the most. A pre-processing stage should be investigated for the evolutionary methods in order to improve performance. Discrete versions of the optimisation methods should be investigated to further improve computational performance.