By the same authors

A Robust Method for Estimating Projective Transformations Using Genetic Algorithms

Research output: Chapter in Book/Report/Conference proceedingConference contribution



Publication details

Title of host publicationProceedings of the IADIS International Conference Computer Graphics and Visualization 2007
DatePublished - 1 Jul 2007
Number of pages5
Original languageEnglish


This paper presents a robust method which provides quantitative estimates of the projective transformations between two successive overlapping images using genetic algorithms. In this method, roulette selection and total arithmetic crossover are applied based on real number encoding. Then an adaptive mutation operator is used to preserve the best solutions.
The experimental results show that the normalized registration error of the final solution exhibits a significant improvement over those obtained by direct search approaches to such problems. Also, in contrast to other popular approaches such as the least-squares and Levenberg-Marquardt algorithms, this algorithm can escape from local extrema and can potentially realize the global optimum.

    Research areas

  • Genetic Algorithms, Crossover, Mutation, Projective Transformation

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