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ScienceAsia 48S (2022): 1-11 |doi: 10.2306/scienceasia1513-1874.2022.S001


Effect of optimization framework on rigid and non-rigid multimodal image registration


Sayan Chakrabortya, Ratika Pradhana, Nilanjan Deyb, Rubén González Crespoc,*, João Manuel R.S. Tavaresd

 
ABSTRACT:     The process of transforming or aligning two images is known as image registration. In the present era, image registration is one of the most popular transformation tools in case of, for example, satellite as well as medical imaging analysis. Images captured by difference devices that can be processed under same registration model are called multimodal images. In this work, we present a multimodal image registration framework, upon which ant colony optimization (ACO) and flower pollination algorithms (FPA), which are two meta heuristics algorithms, are applied in order to improve the performance of a proposed rigid and non-rigid multimodal registration framework and decrease its processing time. The results of the ACO and FPA based framework were compared against particle swarm optimization and Genetic algorithm-based framework's results and seem to be promising.

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a Department of Computer Applications, Sikkim Manipal Institute of Technology, Sikkim 737136 India
b Department of Computer Science and Engineering, JIS University, Kolkata, West Bengal 700109 India
c Universidad Internacional de La Rioja, Logroño 26006 Spain
d Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Industrial, Departamento de Engenharia Mecãnica, Faculdade de Engenharia, Universidade do Porto, Porto 4200-465 Portugal

* Corresponding author, E-mail: ruben.gonzalez@unir.net

Received 27 Jul 2021, Accepted 14 Aug 2021