By Topic

IET Computer Vision

Issue 3 • Date September 2010

Filter Results

Displaying Results 1 - 7 of 7
  • Height estimation from monocular image sequences using dynamic programming with explicit occlusions

    Publication Year: 2010, Page(s):149 - 161
    Cited by:  Papers (3)
    IEEE is not the copyright holder of this material | Click to expandAbstract | PDF file iconPDF (1032 KB)

    In this study, the authors propose a novel algorithm to estimate the heights of objects from monocular aerial images taken from mobile platforms such as unmanned aerial vehicles and small airplanes. Sequential images captured by a single camera mounted on a mobile platform contain 3D information of objects. In this study, the authors propose to use illumination normalisation to reduce illumination... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Statistical interpretation of non-local means

    Publication Year: 2010, Page(s):162 - 172
    Cited by:  Papers (7)
    IEEE is not the copyright holder of this material | Click to expandAbstract | PDF file iconPDF (706 KB)

    Noise filtering is a common step in image processing, and is particularly effective in improving the subjective quality of images. A large number of techniques have been developed, many of which concentrate on the problem of removing noise without damaging small structures such as edges. One recent approach that demonstrates empirical merit is the non-local means (NLM) algorithm. However, in order... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Preserving global and local information - a combined approach for recognising face images

    Publication Year: 2010, Page(s):173 - 182
    IEEE is not the copyright holder of this material | Click to expandAbstract | PDF file iconPDF (393 KB)

    Face recognition can significantly impact authentication, monitoring and indexing applications. Much research on face recognition using global and local information has been done earlier. By using global feature preservation techniques like principal component analysis (PCA) and linear discriminant analysis (LDA), the authors can effectively preserve only the Euclidean structure of face space that... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Aspect coherence for graph-based semantic image labelling

    Publication Year: 2010, Page(s):183 - 194
    IEEE is not the copyright holder of this material | Click to expandAbstract | PDF file iconPDF (712 KB)

    In image semantic segmentation a semantic category label is associated to each image pixel. This classification problem is characterised by pixel dependencies at different scales. On a small-scale pixel correlation is related to object instance sharing, whereas on a middle- and large scale to category co-presence and relative location constraints. The contribution of this study is two-fold. First,... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Face recognition using enhanced linear discriminant analysis

    Publication Year: 2010, Page(s):195 - 208
    Cited by:  Papers (1)
    IEEE is not the copyright holder of this material | Click to expandAbstract | PDF file iconPDF (1303 KB)

    There are two fundamental problems with the linear discriminant analysis (LDA) for face recognition. First one is LDA is not stable because of the small training sample size problem. The other is that it would collapse the data samples of different classes into one single cluster when the class distributions are multimodal. An enhanced LDA method is proposed to overcome these two problems. The bet... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Multimodal biometric method based on vein and geometry of a single finger

    Publication Year: 2010, Page(s):209 - 217
    Cited by:  Papers (3)
    IEEE is not the copyright holder of this material | Click to expandAbstract | PDF file iconPDF (673 KB)

    There are limits to a single biometric observation such as variation in an individual biometric feature due to the condition of a sensor, the health condition of a human, illumination variation and so on. To overcome such limitations, the authors propose a new multimodal biometric approach integrating finger vein recognition and finger geometry recognition at the score level. The method presents t... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Modelling visual saliency using degree centrality

    Publication Year: 2010, Page(s):218 - 229
    Cited by:  Papers (5)
    IEEE is not the copyright holder of this material | Click to expandAbstract | PDF file iconPDF (961 KB)

    Visual attention is an indispensable component of complex vision tasks. A multi-scale, complex network-based approach for determining visual saliency is described. It uses degree centrality (conceptually and computationally the simplest among all the centrality measures) over a network of image regions to form a saliency map. The regions used in the network are multiscale in nature with scale sele... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.

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