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IET Computer Vision

Issue 4 • July 2011

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Displaying Results 1 - 7 of 7
  • Digital Image Computing Techniques and Applications (DICTA) Conference 2009

    Publication Year: 2011, Page(s): 191
    IEEE is not the copyright holder of this material | Click to expandAbstract | PDF file iconPDF (42 KB)

    The conference Digital Image Computing Techniques and Applications (DICTA) is held in December every year in Australia or New Zealand and is the flagship conference hosted by the Australian Pattern Recognition Society (APRS). The conference provides a forum for researchers in the antipodes as well as Southeast Asia and often from farther afield to present and discuss their work within the broadly ... View full abstract»

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  • Particle filter to track multiple people for visual surveillance

    Publication Year: 2011, Page(s):192 - 200
    Cited by:  Papers (5)
    IEEE is not the copyright holder of this material | Click to expandAbstract | PDF file iconPDF (1004 KB)

    A particle filter (PF) has been recently proposed to detect and track colour objects in video. This study presents an adaptation of the PF to track people in surveillance video. Detection is based on automated background modelling rather than a manually generated object colour model. Furthermore, a labelling method is proposed to create tracks of objects through the scene, rather than unconnected ... View full abstract»

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  • Incremental object matching and detection with Bayesian methods and particle filters

    Publication Year: 2011, Page(s):201 - 210
    IEEE is not the copyright holder of this material | Click to expandAbstract | PDF file iconPDF (1021 KB)

    This study is about object matching, that is, a problem of locating the corresponding points of an object in an image. Conventional approaches to object matching are batch methods, meaning that the methods first learn the object model from a training set of example images that contain instances of the object, and then use the learned object model to match instances of the same object (or object cl... View full abstract»

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  • Texture description in local scale using texton histograms with quadrature filter universal dictionaries

    Publication Year: 2011, Page(s):211 - 221
    IEEE is not the copyright holder of this material | Click to expandAbstract | PDF file iconPDF (686 KB)

    An inherent property to the texture patterns is that they are only meaningful in an appropriate range of scales. Taking this into account, the description of the texture patterns should be limited to its meaningful scales. This assumption motivates the research on local-scale texture description. In this study, a method for the extraction and description of texture features using local scale is pr... View full abstract»

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  • Wide baseline correspondence extraction beyond local features

    Publication Year: 2011, Page(s):222 - 231
    IEEE is not the copyright holder of this material | Click to expandAbstract | PDF file iconPDF (690 KB)

    Robust, affine covariant, feature extractors provide a means to extract correspondences between images captured by widely separated cameras. Advances in wide baseline correspondence extraction require looking beyond the robust feature extraction and matching approach. This study examines new techniques of extracting correspondences that take advantage of information contained in affine feature mat... View full abstract»

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  • Paper fingerprinting using alpha-masked image matching

    Publication Year: 2011, Page(s):232 - 243
    IEEE is not the copyright holder of this material | Click to expandAbstract | PDF file iconPDF (861 KB)

    In this study, the authors examine the process of authenticating paper media using the unique fibre structure of a piece of paper (the so-called `paper fingerprint`) In particular, the authors look at methods to authenticate a paper fingerprint when text has been printed over the authentication zone. The authors show how alpha-masked correlation can be applied to this problem and develop a modific... View full abstract»

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  • Correlating fourier descriptors of local patches for road sign recognition

    Publication Year: 2011, Page(s):244 - 254
    Cited by:  Papers (2)
    IEEE is not the copyright holder of this material | Click to expandAbstract | PDF file iconPDF (1100 KB)

    The Fourier descriptors (FDs) is a classical but still popular method for contour matching. The key idea is to apply the Fourier transform to a periodic representation of the contour, which results in a shape descriptor in the frequency domain. FDs are most commonly used to compare object silhouettes and object contours; the authors instead use this well-established machinery to describe local reg... View full abstract»

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Aims & Scope

IET Computer Vision seeks original research papers in a wide range of areas of computer vision. The vision of the journal is to publish the highest quality research work that is relevant and topical to the field, but not forgetting those works that aim to introduce new horizons and set the agenda for future avenues of research in Computer Vision.

Full Aims & Scope

Meet Our Editors

Editor-in-Chief
Majid Mirmehdi
University of Bristol
UK

Publisher
Editorial Assistant
IET Research Journals
Michael Faraday House
Six Hills Way
Stevenage  SG1 2AY  SG1 2AY  United Kingdom
iet_cvi@theiet.org