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Feature detection in scale-space

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Scale-Space Theory in Computer Vision

Part of the book series: The Springer International Series in Engineering and Computer Science ((SECS,volume 256))

Abstract

The treatment in previous chapters gives a formal justification for using linear filtering as an initial step in early processing of image data. More important, it provides a catalogue of what filter kernels are natural to use, as well as an extensive theoretical explanation of how smoothing kernels of different order and at different scales can be related. In particular, the discretization problem is extensively treated. This forms the basis for a theoretically well-founded modelling of the smoothing operation.

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© 1994 Springer Science+Business Media Dordrecht

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Lindeberg, T. (1994). Feature detection in scale-space. In: Scale-Space Theory in Computer Vision. The Springer International Series in Engineering and Computer Science, vol 256. Springer, Boston, MA. https://doi.org/10.1007/978-1-4757-6465-9_6

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  • DOI: https://doi.org/10.1007/978-1-4757-6465-9_6

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4419-5139-7

  • Online ISBN: 978-1-4757-6465-9

  • eBook Packages: Springer Book Archive

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