Abstract
In this paper we propose a novel method for affine registration of images and point patterns. The method is non-iterative and it directly utilizes the intensity distribution of the images or the spatial distribution of points in the patterns. The method can be used to align images of isolated objects or sets of 2D and 3D points. For Euclidean and similarity transformations the additional contraints can be easily embedded in the algorithm. The main advantage of the proposed method is its efficiency since the computational complexity is only linearly proportional to the number of pixels in the images (or to the number of points in the sets).In the experiments we have compared our method with some other non-feature-based registration methods and investigated its robustness. The experiments show that the proposed method is relatively robust so that it can be applied in practical circumstances.
Keywords
- Binary Image
- Similarity Transformation
- Grayscale Image
- Point Pattern
- Registration Method
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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© 2005 Springer-Verlag Berlin Heidelberg
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Kannala, J., Rahtu, E., Heikkilä, J., Salo, M. (2005). A New Method for Affine Registration of Images and Point Sets. In: Kalviainen, H., Parkkinen, J., Kaarna, A. (eds) Image Analysis. SCIA 2005. Lecture Notes in Computer Science, vol 3540. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11499145_25
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DOI: https://doi.org/10.1007/11499145_25
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-26320-3
Online ISBN: 978-3-540-31566-7
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