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Affine image registration transformation estimation using a real coded genetic algorithm with SBX

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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Affine image registration transformation estimation using a real coded genetic algorithm with SBX. / Bazargani, Mosab; Anjos, António; Lobo, Fernando et al.
Proceedings of the 14th Annual Conference Companion on Genetic and Evolutionary Computation. New York, NY, USA: Association for Computing Machinery, 2012. p. 1459–1460 (GECCO '12).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

HarvardHarvard

Bazargani, M, Anjos, A, Lobo, F, Mollahosseini, A & Shahbazkia, H 2012, Affine image registration transformation estimation using a real coded genetic algorithm with SBX. in Proceedings of the 14th Annual Conference Companion on Genetic and Evolutionary Computation. GECCO '12, Association for Computing Machinery, New York, NY, USA, pp. 1459–1460. https://doi.org/10.1145/2330784.2330990

APA

Bazargani, M., Anjos, A., Lobo, F., Mollahosseini, A., & Shahbazkia, H. (2012). Affine image registration transformation estimation using a real coded genetic algorithm with SBX. In Proceedings of the 14th Annual Conference Companion on Genetic and Evolutionary Computation (pp. 1459–1460). (GECCO '12). Association for Computing Machinery. https://doi.org/10.1145/2330784.2330990

CBE

Bazargani M, Anjos A, Lobo F, Mollahosseini A, Shahbazkia H. 2012. Affine image registration transformation estimation using a real coded genetic algorithm with SBX. In Proceedings of the 14th Annual Conference Companion on Genetic and Evolutionary Computation. New York, NY, USA: Association for Computing Machinery. pp. 1459–1460. (GECCO '12). https://doi.org/10.1145/2330784.2330990

MLA

Bazargani, Mosab et al. "Affine image registration transformation estimation using a real coded genetic algorithm with SBX". Proceedings of the 14th Annual Conference Companion on Genetic and Evolutionary Computation. GECCO '12. New York, NY, USA: Association for Computing Machinery. 2012, 1459–1460. https://doi.org/10.1145/2330784.2330990

VancouverVancouver

Bazargani M, Anjos A, Lobo F, Mollahosseini A, Shahbazkia H. Affine image registration transformation estimation using a real coded genetic algorithm with SBX. In Proceedings of the 14th Annual Conference Companion on Genetic and Evolutionary Computation. New York, NY, USA: Association for Computing Machinery. 2012. p. 1459–1460. (GECCO '12). doi: 10.1145/2330784.2330990

Author

Bazargani, Mosab ; Anjos, António ; Lobo, Fernando et al. / Affine image registration transformation estimation using a real coded genetic algorithm with SBX. Proceedings of the 14th Annual Conference Companion on Genetic and Evolutionary Computation. New York, NY, USA : Association for Computing Machinery, 2012. pp. 1459–1460 (GECCO '12).

RIS

TY - GEN

T1 - Affine image registration transformation estimation using a real coded genetic algorithm with SBX

AU - Bazargani, Mosab

AU - Anjos, António

AU - Lobo, Fernando

AU - Mollahosseini, Ali

AU - Shahbazkia, Hamid

PY - 2012/7/7

Y1 - 2012/7/7

N2 - We describe the application of a real coded genetic algorithm (GA) to align two or more 2-D images by means of image registration. The proposed search strategy is a transformation parameters-based approach involving the affine transform. The real coded GA uses Simulated Binary Crossover (SBX). In addition, we propose a new technique for matching points between a warped and static images by using a randomized ordering when visiting the points during the matching procedure. The results confirm the usefulness of the proposed noisy objective function and the suitability of SBX as a recombination operator for this type of problem.

AB - We describe the application of a real coded genetic algorithm (GA) to align two or more 2-D images by means of image registration. The proposed search strategy is a transformation parameters-based approach involving the affine transform. The real coded GA uses Simulated Binary Crossover (SBX). In addition, we propose a new technique for matching points between a warped and static images by using a randomized ordering when visiting the points during the matching procedure. The results confirm the usefulness of the proposed noisy objective function and the suitability of SBX as a recombination operator for this type of problem.

KW - affine transform

KW - genetic algorithms

KW - image registration

KW - point-pattern matching

KW - simulated binary crossover

U2 - 10.1145/2330784.2330990

DO - 10.1145/2330784.2330990

M3 - Conference contribution

SN - 9781450311786

T3 - GECCO '12

SP - 1459

EP - 1460

BT - Proceedings of the 14th Annual Conference Companion on Genetic and Evolutionary Computation

PB - Association for Computing Machinery

CY - New York, NY, USA

ER -