Neural Network Based Image Registration Using Synthetic Reference Image Rotation

  • S. Phandi
  • C. Shunmuga VelayuthamEmail author
Conference paper
Part of the Lecture Notes in Computational Vision and Biomechanics book series (LNCVB, volume 30)


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.


Feature extraction SURF Neural network Affine transformation Image registration 


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringAmrita School of Engineering, CoimbatoreAmrita Vishwa VidyapeethamIndia

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