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Scale selection
KTH, School of Computer Science and Communication (CSC), Computational Biology, CB.ORCID iD: 0000-0002-9081-2170
2014 (English)In: Computer Vision: A Reference Guide / [ed] Katsushi Ikeuchi, Springer US , 2014, 701-713 p.Chapter in book (Refereed)
Abstract [en]

The notion of scale selection refers to methods for estimating characteristic scales in image data and for automatically determining locally appropriate scales in a scale-space representation, so as to adapt subsequent processing to the local image structure and compute scale invariant image features and image descriptors.

An essential aspect of the approach is that it allows for a bottom-up determination of inherent scales of features and objects without first recognizing them or delimiting alternatively segmenting them from their surrounding.

Scale selection methods have also been developed from other viewpoints of performing noise suppression and exploring top-down information.

Place, publisher, year, edition, pages
Springer US , 2014. 701-713 p.
Keyword [en]
scale-space, feature detection, scale invariance, interest point detection, blob detection, corner detection, edge detection, ridge detection, frequency estimation, feature tracking, image-based recognition, object recognition
National Category
Computer Science Computer Vision and Robotics (Autonomous Systems)
URN: urn:nbn:se:kth:diva-52432DOI: 10.1007/978-0-387-31439-6_242ISBN: 978-0-387-30771-8ISBN: 978-0-387-31439-6OAI: diva2:466487
Swedish Research Council, 2010-4766Knut and Alice Wallenberg Foundation

QC 20130111

Available from: 2011-12-16 Created: 2011-12-16 Last updated: 2014-06-30Bibliographically approved

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