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Volume 143
Issue 4
IEE Proceedings - Vision, Image and Signal Processing
Volume 143, Issue 4, August 1996
Volumes & issues:
Volume 143, Issue 4
August 1996
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- Author(s): R.-C. Lo and W.H. Tsai
- Source: IEE Proceedings - Vision, Image and Signal Processing, Volume 143, Issue 4, p. 201 –209
- DOI: 10.1049/ip-vis:19960448
- Type: Article
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p.
201
–209
(9)
A new approach to 2-dimensional (2D) colour-image detection and matching using a modified version of the generalised Hough transform (GHT) is proposed. In the conventional GHT, the useful colour information existing in the input image and the relationship between each pixel and its neighbourhood are not used. Furthermore, lighting changes in the image are not usually considered. Therefore, the conventional GHT is seldom applied to colour images. In the proposed approach, lighting changes are removed using normalised colour values. Next, certain critical pixels of an input colour image whose neighbourhoods have larger variances of normalised colour values are extracted. For each critical pixel, a feature vector, which includes the normalised colour values of the pixel as well as those of the pixel's neighbours, is then constructed. A modified voting rule for the GHT is therefore proposed which is based on a similarity-measure function of the feature vectors. High maximum peaks in the cell array are searched finally as the result. The proposed method is robust for colour-image detection and matching in noisy, occlusive, and lighting-change environments, as demonstrated by experimental results. - Author(s): H.-M. Suen and J.-F. Wang
- Source: IEE Proceedings - Vision, Image and Signal Processing, Volume 143, Issue 4, p. 210 –216
- DOI: 10.1049/ip-vis:19960325
- Type: Article
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p.
210
–216
(7)
Given the mass of printed documents today, an automated entry system is highly desirable. Many techniques focusing on processing monochrome documents have been proposed in the past years but few techniques have been proposed for dealing with colour-printed documents. The authors discuss the processing of colour-printed documents in 24-bit true colour images and propose an approach for extracting text strings from them. Due to the very large amount of data in a 24-bit true colour image, processing is usually very time consuming. To reduce the computational complexity and thus speed up processing, the original colour image is first transformed into a binary image of edge representation for page segmentation. Then a new method is used to identify the text blocks. Finally, all the identified text blocks are transformed into white-background/black-text binary images for an OCR system. The proposed approach was implemented and tested on a Pentium/90 PC and experimental results have demonstrated its feasibility. - Author(s): M.-J. Chen ; L.-G. Chen ; K.-N. Cheng ; M.C. Chen
- Source: IEE Proceedings - Vision, Image and Signal Processing, Volume 143, Issue 4, p. 217 –222
- DOI: 10.1049/ip-vis:19960541
- Type: Article
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p.
217
–222
(6)
Execution latency and I/O bandwidth play essential roles in determining the effectiveness and the cost of a parallel hardware implementation for block-matching motion estimation algorithms. Unfortunately, almost all traditional architecture designs, e.g. the two-dimensional mesh-connected systolic array architecture (2DMCSA), and the tree-type structure (TTS), fail to take these two factors into account simultaneously. As a result, they suffer from either large execution latency or huge input bandwidth requirements. The authors propose a family of tree/linear architectures, which efficiently optimise the total implementation cost by combining the merits of the 2DMCSA and the TTS. Moreover, to facilitate hardware designs, the authors present the tree-cut techniques and the on-chip buffer design method to meet computational demands of various video compression applications. Since the proposed architectures are capable of executing the exhaustive search and the fast search block-matching algorithms, they offer relatively flexible and cost-effective hardware solutions for a wide range of video coding systems, including CD-ROM, portable visual communications systems and high-definition TV. - Author(s): B.P. Milner and S.V. Vaseghi
- Source: IEE Proceedings - Vision, Image and Signal Processing, Volume 143, Issue 4, p. 223 –231
- DOI: 10.1049/ip-vis:19960577
- Type: Article
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p.
223
–231
(9)
The use of a speech recognition system with telephone channel environments, or different microphones, requires channel equalisation. In speech recognition, the speech model provides a bank of statistical information that can be used in the channel identification and equalisation process. The authors consider HMM-based channel equalisation, and present results demonstrating that substantial improvement can be obtained through the equalisation process. An alternative method, for speech recognition, is to use a feature set which is more robust to channel distortion. Channel distortions result in an amplitude tilt of the speech cepstrum, and therefore differential cepstral features provide a measure of immunity to channel distortions. In particular the cepstral–time feature matrix, in addition to providing a framework for representing speech dynamics, can be made robust to channel distortions. The authors present results demonstrating that a major advantage of cepstral–time matrices is their channel insensitive character.
Colour image detection and matching using modified generalised Hough transform
Text string extraction from images of colour-printed documents
Efficient hybrid tree/linear array architectures for block-matching motion estimation algorithms
Bayesian channel equalisation and robust features for speech recognition
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- Author(s): Y. Nakazawa ; T. Komatsu ; T. Saito
- Source: IEE Proceedings - Vision, Image and Signal Processing, Volume 143, Issue 4, p. 234 –240
- DOI: 10.1049/ip-vis:19960691
- Type: Article
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p.
234
–240
(7)
The authors propose an image-processing-based approach towards the development of a super-high-resolution image acquisition system. Imaging methods based on this approach can be classified into two main categories: a spatial integration imaging method and a temporal integration imaging method. With regard to the spatial integration imaging method, the authors have recently presented a method for acquiring an improved-resolution image by integrating multiple images taken simultaneously with multiple different cameras. They develop their work, aiming at a particular class of application where a user indicates a region of interest (ROI) on an observed image in advance, and apply a prototypal temporal integration imaging method. The prototypal temporal integration imaging method does not involve global image segmentation, but uses a subpixel registration algorithm which describes an image warp within the ROI, with subpixel accuracy, as a deformation of quadrilateral patches. The method then performs a subpixel registration by warping an observed image with the warping function recovered from the deformed quadrilateral patches. Experimental simulations demonstrate that the temporal integration imaging is promising as a basic means of high resolution imaging. - Author(s): E.C. Di Mauro ; T.F. Cootes ; G.J. Page ; C.B. Jackson
- Source: IEE Proceedings - Vision, Image and Signal Processing, Volume 143, Issue 4, p. 241 –249
- DOI: 10.1049/ip-vis:19960692
- Type: Article
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p.
241
–249
(9)
The authors present an overview of an ‘inspection and control’ package to perform automatic quality control of industrial components, specifically electronic circuit boards. This application has grown out of a set of tools designed initially to aid the development of point distribution models (PDMs) and grey-level models (GLMs) pioneered at the Wolfson Image Analysis Unit in Manchester. These models are both generic and specific. Generic, because they can be applied to most image classification problems; specific, because they aim at the full interpretation of the variability of the objects to be modelled. The underlying vision processing techniques are based on statistical pattern matching. Two synergetic approaches have been followed. The system is trained to recognise the components from either their shape or their grey level appearance or both. - Author(s): J.J.K. Ó Ruanaidh ; W.J. Dowling ; F.M. Boland
- Source: IEE Proceedings - Vision, Image and Signal Processing, Volume 143, Issue 4, p. 250 –256
- DOI: 10.1049/ip-vis:19960711
- Type: Article
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p.
250
–256
(7)
A watermark is an invisible mark placed on an image that is designed to identify both the source of an image as well as its intended recipient. The authors present an overview of watermarking techniques and demonstrate a solution to one of the key problems in image watermarking, namely how to hide robust invisible labels inside grey scale or colour digital images. - Author(s): S. Girard ; J.-M. Dinten ; B. Chalmond
- Source: IEE Proceedings - Vision, Image and Signal Processing, Volume 143, Issue 4, p. 257 –264
- DOI: 10.1049/ip-vis:19960689
- Type: Article
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p.
257
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(8)
The authors address the problem of identifying the projection of an object from incomplete data extracted from its radiographic image. They assume that the unknown object is a particular sample of a flexible object. Their approach consists first in designing a deformation model able to represent and to simulate a great variety of samples of the flexible object radiographic projection. This modellisation is achieved using a training set of complete data. Then, given the incomplete data, the identification task consists in estimating the observed object using the deformation model. The proposed modelling extracts from the training set, not only the deformation modes, but also other relevant information (such as probability distributions on the deformations, relations between deformations) to use it to regularise the identification step. - Author(s): S. Dickson ; B.T. Thomas ; W.J.P. Mackeown ; P. Goddard
- Source: IEE Proceedings - Vision, Image and Signal Processing, Volume 143, Issue 4, p. 265 –272
- DOI: 10.1049/ip-vis:19960690
- Type: Article
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p.
265
–272
(8)
A method is described for the detection and localisation of benign tumours from head MR images. Detection is carried out at the pixel level using a neural network based approach. The results of this are fused with regions, formed by a robust edge-region segmentation, to enable identification of regions corresponding to part of a tumour. The method described achieves a high sensitivity and specificity, and all tumours in the example set are detected.
Temporal integration method for image-processing-based super-high-resolution image acquisition
Check! A generic and specific industrial inspection tool
Watermarking digital images for copyright protection
Building and training radiographic models for flexible object identification from incomplete data
Computer vision applied to the detection and localisation of acoustic neuromas from head MR images
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