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IET Computer Vision

Issue 3 • September 2009

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Displaying Results 1 - 6 of 6
  • Vision-based monitoring method using gray relational analysis

    Publication Year: 2009, Page(s):103 - 111
    Cited by:  Papers (4)
    IEEE is not the copyright holder of this material | Click to expandAbstract | PDF file iconPDF (630 KB)

    Intelligent surveillance system has become an important research topic in the field of computer vision. The authors propose a monitoring method based on the cellular model to monitor human activities in the indoor environment. The measured area of an indoor room is divided into several unit areas in which each unit area is considered as a simple cell in the cellular model. A rectangular box is the... View full abstract»

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  • Combining classifiers through fuzzy cognitive maps in natural images

    Publication Year: 2009, Page(s):112 - 123
    Cited by:  Papers (2)
    IEEE is not the copyright holder of this material | Click to expandAbstract | PDF file iconPDF (512 KB)

    A new automatic hybrid classifier for natural images by combining two base classifiers through the fuzzy cognitive maps (FCMs) approach is presented in this study. The base classifiers used are fuzzy clustering (FC) and the parametric Bayesian (BP) method. During the training phase, different partitions are established until a valid partition is found. Partitioning and validation are two automatic... View full abstract»

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  • Wand-based calibration of 3D kinematic system

    Publication Year: 2009, Page(s):124 - 129
    IEEE is not the copyright holder of this material | Click to expandAbstract | PDF file iconPDF (200 KB)

    This study proposes a method to calibrate 3D kinematic systems. The authors briefly address typical wand-based calibration, that is, calibration using a rigid bar, both from the computational point of view and the procedural perspective, and then they define their alternative way of calibration. The proposed method takes advantage of a feature of the presently used calibration tools, that is, the ... View full abstract»

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  • Robust face recognition using posterior union model based neural networks

    Publication Year: 2009, Page(s):130 - 142
    Cited by:  Papers (6)
    IEEE is not the copyright holder of this material | Click to expandAbstract | PDF file iconPDF (670 KB)

    Face recognition with unknown, partial distortion and occlusion is a practical problem, and has a wide range of applications, including security and multimedia information retrieval. The authors present a new approach to face recognition subject to unknown, partial distortion and occlusion. The new approach is based on a probabilistic decision-based neural network, enhanced by a statistical method... View full abstract»

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  • Estimating fibre orientation in spruce using lighting direction

    Publication Year: 2009, Page(s):143 - 158
    IEEE is not the copyright holder of this material | Click to expandAbstract | PDF file iconPDF (1603 KB)

    Softwood is almost entirely composed of fibres and its physical properties depend on their orientation. A method is proposed to estimate the average fibre orientation at each pixel in the inspection image. In this study it is shown that finished wood has distinctive reflectance properties that are a consequence of the microstructure of the wood surface. If the fibres lie parallel to the image plan... View full abstract»

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  • Discriminant analysis based on modified generalised singular value decomposition and its numerical error analysis

    Publication Year: 2009, Page(s):159 - 173
    Cited by:  Papers (1)
    IEEE is not the copyright holder of this material | Click to expandAbstract | PDF file iconPDF (256 KB)

    Generalised singular value decomposition (GSVD) has been used in the literature for linear discriminant analysis (LDA) to solve the small sample size problem in pattern recognition. However, this method, commonly known as LDA/GSVD algorithm, suffers from excessive computational load when the sample dimension is high. Here the GSVD framework used in the LDA/GSVD algorithm is modified by replacing t... 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