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Scale-Invariant Feature Transform (SIFT)

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Digital Image Processing

Part of the book series: Texts in Computer Science ((TCS))

Abstract

Many real applications require the localization of reference positions in one or more images, for example, for image alignment, removing distortions, object tracking, 3D reconstruction, etc. We have seen that corner points1 can be located quite reliably and independent of orientation. However, typical corner detectors only provide the position and strength of each candidate point, they do not provide any information about its characteristic or “identity” that could be used for matching. Another limitation is that most corner detectors only operate at a particular scale or resolution, since they are based on a rigid set of filters.

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© 2016 Springer-Verlag London

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Burger, W., Burge, M.J. (2016). Scale-Invariant Feature Transform (SIFT). In: Digital Image Processing. Texts in Computer Science. Springer, London. https://doi.org/10.1007/978-1-4471-6684-9_25

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  • DOI: https://doi.org/10.1007/978-1-4471-6684-9_25

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  • Publisher Name: Springer, London

  • Print ISBN: 978-1-4471-6683-2

  • Online ISBN: 978-1-4471-6684-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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