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Robust Multi-scale Extraction of Blob Features

  • Per-Erik Forssén
  • Gösta Granlund
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2749)

Abstract

This paper presents a method for detection of homogeneous regions in grey-scale images, representing them as blobs. In order to be fast, and not to favour one scale over others, the method uses a scale pyramid. In contrast to most multi-scale methods this one is non-linear, since it employs robust estimation rather than averaging to move through scale-space. This has the advantage that adjacent and partially overlapping clusters only affect each other’s shape, not each other’s values. It even allows blobs within blobs, to provide a pyramid blob structure of the image.

Keywords

Label Image Channel Vector Pepper Noise Channel Image Channel Representation 
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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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Per-Erik Forssén
    • 1
  • Gösta Granlund
    • 1
  1. 1.Computer Vision LaboratoryLinköping UniversityLinköpingSweden

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