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Online ISSN 1751-9667 Print ISSN 1751-9659

IET Image Processing

Volume 2, Issue 1, February 2008

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Volume 2, Issue 1

February 2008

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    • Video texture modelling and synthesis using fractal processes
      • Author(s): P. Campisi ; E. Maiorana ; A. Neri ; G. Scarano
      • Source: IET Image Processing, Volume 2, Issue 1, p. 1 –17
      • DOI:  10.1049/iet-ipr:20065010
      • Type: Article
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      • p. 1 –17 (17)
        The authors propose a new approach for the synthesis of natural video textures using a fractal-based approach. Specifically, a video texture is modelled according to the three-dimensional (3D) extended self-similar (ESS) model introduced, which generalises the fractional Brownian motion process. The analysis of original video textures is based on the estimation of the autocorrelation functions (ACFs) of the textures' increments. The 3D-ESS model is then used to synthesise a process whose increments have the same ACFs of the given prototype. The synthesis is accomplished by generalising to the 3D case the incremental Fourier synthesis algorithm. Experimental results for the analysis and synthesis of natural video textures are eventually provided.
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      Fast centre–surround contrast modification
      • Author(s): V. Vonikakis ; I. Andreadis ; A. Gasteratos
      • Source: IET Image Processing, Volume 2, Issue 1, p. 19 –34
      • DOI:  10.1049/iet-ipr:20070012
      • Type: Article
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      • p. 19 –34 (16)
        A new algorithm for fast contrast modification of standard dynamic range (SDR) images (8 bits/channel) is presented. Its thrust is to enhance the contrast in the under-/over-exposed regions of SDR images, caused by the low dynamic range of the capturing device. It is motivated by the attributes of the shunting centre–surround cells of the human visual system. The main advantage of the proposed algorithm is its O(N) complexity which results in very fast execution, even when executed on a conventional personal computer (0.2 s/frame for a 640×480 pixel resolution on a 3 GHz Pentium 4). Thus, it moderately increases the computational burden if it is used as a pre-processing stage for other image processing algorithms. The proposed method is compared with other established algorithms, which can enhance the contrast in the under-/over-exposed regions of SDR images: the multi-scale Retinex with colour rendition, the McCann Retinex (McCann99), the rational mapping function and the automatic colour equalisation. The results obtained by this comparison indicate that the proposed algorithm exhibits at least comparable results in contrast modification tasks to the other algorithms, in significantly reduced execution times.
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      Discrete image modelling for piecewise constant segmentation by artificial neural networks
      • Author(s): A. De Santis  and  D. Iacoviello
      • Source: IET Image Processing, Volume 2, Issue 1, p. 37 –47
      • DOI:  10.1049/iet-ipr:20070039
      • Type: Article
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      • p. 37 –47 (11)
        The problem of an image best approximation within the class of piecewise constant functions is considered. This allows a simpler data representation with a lower number of grey levels while retaining all information relevant to the particular application considered. The approximant can be found by solving a segmentation problem. The search for a solution is solved efficiently by training an artificial neural network (ANN) on a suitable set of templates by a standard procedure. The samples of the training alphabet fit the signal's local behaviour in the homogeneous image subregions and in the regions crossed by the edges. Therefore the original image domain is partitioned into disjoint 2D intervals (tiling), and for each one of them, the network selects the alphabet element closest to the corresponding image component. The main motivation of this work consists in devising a methodology suitable for real-time applications; indeed, the ANN tool is attractive for a hardware implementation.
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      Optical coherence tomography used for security and fingerprint-sensing applications
      • Author(s): S. Chang ; Y. Cheng ; K.V. Larin ; Y. Mao ; S. Sherif ; C. Flueraru
      • Source: IET Image Processing, Volume 2, Issue 1, p. 48 –58
      • DOI:  10.1049/iet-ipr:20070021
      • Type: Article
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      • p. 48 –58 (11)
        Optical coherence tomography (OCT) is an emerging technology for high-resolution cross-sectional imaging of three-dimensional structures. In the past, OCT systems have been used mainly for medical applications, especially ophthalmological diagnostics. As the OCT system is capable of exploring the internal features of an object, the authors apply OCT technology to document security and fingerprint-based biometrics by directly retrieving the two-dimensional information form of a multiple-layer information carrier and internal human body objects. Since a typical depth-resolution of an OCT system is of micrometre scale, an information carrier having a volume of 20 mm×20 mm×2 mm could contain 200 mega-pixel images. On other hand, the technologies used in conventional biometrics can be easily fooled and tampered with by using artificial dummies, because these ID features are extracted only from the surface of the skin. Hence the use of OCT to explore the internal biometrics becomes increasingly important.
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