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Neural Network Based Image Registration Using Synthetic Reference Image Rotation

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Proceedings of the International Conference on ISMAC in Computational Vision and Bio-Engineering 2018 (ISMAC-CVB) (ISMAC 2018)

Part of the book series: Lecture Notes in Computational Vision and Biomechanics ((LNCVB,volume 30))

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Abstract

Typical image registration techniques use a set of features from a target and reference images and search in the affine transformation space using a similarity metric. Neural Networks typically have employed two choices—geometric transformations to find correlation between images and a similarity metric. In this paper, however, we have proposed and employed a simple and effective method for image registration using neural networks. The image registration has been formulated as a classification problem. By generating and learning exhaustive synthetic reference image transformations appropriate re-transformation for target image is computed for effective registration. The proposed work is tested on satellite imagery.

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Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, Amrita School of Engineering, Coimbatore, Amrita Vishwa Vidyapeetham, India

    S. Phandi & C. Shunmuga Velayutham

Authors
  1. S. Phandi
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  2. C. Shunmuga Velayutham
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Corresponding author

Correspondence to C. Shunmuga Velayutham .

Editor information

Editors and Affiliations

  1. SCAD Institute of Technology, Palladam, India

    Durai Pandian

  2. Department of Electrical and Computer Engineering, Ryerson University, Toronto, ON, Canada

    Xavier Fernando

  3. School of Computer and Security Science, Edith Cowan University, Joondalup, WA, Australia

    Zubair Baig

  4. Wenzhou Medical University, Wenzhou, China

    Fuqian Shi

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Phandi, S., Shunmuga Velayutham, C. (2019). Neural Network Based Image Registration Using Synthetic Reference Image Rotation. In: Pandian, D., Fernando, X., Baig, Z., Shi, F. (eds) Proceedings of the International Conference on ISMAC in Computational Vision and Bio-Engineering 2018 (ISMAC-CVB). ISMAC 2018. Lecture Notes in Computational Vision and Biomechanics, vol 30. Springer, Cham. https://doi.org/10.1007/978-3-030-00665-5_88

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  • DOI: https://doi.org/10.1007/978-3-030-00665-5_88

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-00664-8

  • Online ISBN: 978-3-030-00665-5

  • eBook Packages: EngineeringEngineering (R0)

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