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Volume 153
Issue 6
IEE Proceedings - Vision, Image and Signal Processing
Volume 153, Issue 6, December 2006
Volumes & issues:
Volume 153, Issue 6
December 2006
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- Author(s): K.N. Macpherson and R.W. Stewart
- Source: IEE Proceedings - Vision, Image and Signal Processing, Volume 153, Issue 6, p. 711 –720
- DOI: 10.1049/ip-vis:20045133
- Type: Article
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p.
711
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(10)
A new algorithm that synthesises multiplier blocks with low hardware requirement suitable for implementation as part of full-parallel finite impulse response (FIR) filters is presented. Although the techniques in use are applicable to implementation on application-specific integrated circuit (ASIC) and Structured ASIC technologies, analysis is performed using field programmable gate array (FPGA) hardware. Fully pipelined, full-parallel transposed-form FIR filters with multiplier block were generated using the new and previous algorithms, implemented on an FPGA target and the results compared. Previous research in this field has concentrated on minimising multiplier block adder cost but the results presented here demonstrate that this optimisation goal does not minimise FPGA hardware. Minimising multiplier block logic depth and pipeline registers is shown to have the greatest influence in reducing FPGA area cost. In addition to providing lower area solutions than existing algorithms, comparisons with equivalent filters generated using the distributed arithmetic technique demonstrate further area advantages of the new algorithm. - Author(s): I.S. Uzun and A. Amira
- Source: IEE Proceedings - Vision, Image and Signal Processing, Volume 153, Issue 6, p. 721 –734
- DOI: 10.1049/ip-vis:20045080
- Type: Article
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p.
721
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(14)
The discrete wavelet transform has taken its place at the forefront of research for the development of signal and image processing applications. These wavelet-based approaches have outperformed existing strategies in many areas including telecommunication, numerical analysis and, most notably, image/video compression. The authors present an investigation into the design and implementation of 1-D and 2-D discrete biorthogonal wavelet transforms (DBWTs) using a field programmable gate array (FPGA)-based rapid prototyping environment. The proposed architectures for DBWTs are scalable, modular and have less area and time complexity when compared with existing structures. FPGA implementation results based on a Xilinx Virtex-2000E device have shown that the proposed system provides an efficient solution for the processing of DBWTs in real-time. - Author(s): D. Wang ; N. Yu ; Y. Gao ; R. Zhang
- Source: IEE Proceedings - Vision, Image and Signal Processing, Volume 153, Issue 6, p. 735 –738
- DOI: 10.1049/ip-vis:20045086
- Type: Article
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735
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A correlation-inheriting vector quantisation (VQ) image coding algorithm is presented to re-encode the output indices of VQ after analysing the correlation inheritance of the indices' neighbourhood. Simulation results indicate that this algorithm can compact the VQ index to achieve an ∼21:1 compression ratio on average. In accordance with this new algorithm, an efficient very large scale integration architecture is also derived that, after synthesis, achieves a system clock rate of 110 MHz using a 0.35 µm complementary metal-oxide-semiconductor standard library. - Author(s): F. Bensaali and A. Amira
- Source: IEE Proceedings - Vision, Image and Signal Processing, Volume 153, Issue 6, p. 739 –746
- DOI: 10.1049/ip-vis:20045076
- Type: Article
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p.
739
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(8)
3D graphics performance is increasing faster than any other computing application. Almost all PC systems now include 3D graphics accelerators for games, computer aided design or visualisation applications. This article investigates the suitability of field programmable gate array devices as an accelerator for implementing 3D affine transformations. Proposed solution based on processing large matrix multiplication have been implemented, for large 3D models, on the RC1000 Celoxica board based development platform using Handel-C. Outstanding results have been obtained for the acceleration of 3D transformations using fixed and floating-point arithmetic. - Author(s): M.A. McKeown ; I.A.B. Lindsay ; D.G.M. Cruickshank ; J.S. Thompson ; S.A. Farson ; Y. Hu
- Source: IEE Proceedings - Vision, Image and Signal Processing, Volume 153, Issue 6, p. 747 –753
- DOI: 10.1049/ip-vis:20045063
- Type: Article
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p.
747
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(7)
The development of a re-scalable hardware implementation of a V-BLAST (Vertical Bell Labs Space–Time) multiple input multiple output system for future wireless communications systems is described. Re-scalability will support rapid prototyping of such systems. A floating-point model of the re-scalable system is constructed to guide the development of a fixed-point model, and subsequently a re-scalable hardware implementation. The system uses the Gauss–Jordan elimination method to perform channel matrix inversion and altering the division-by-zero threshold in this matrix inversion process is shown to have a significant effect on bit error rate performance results. The re-scalable hardware implementation is described in a hardware description language in the form of an intellectual property block and several V-BLAST systems are synthesised onto field programmable gate arrays.
Area efficient FIR filters for high speed FPGA implementation
Framework for FPGA-based discrete biorthogonal wavelet transforms implementation
Effective correlation vector quantisation algorithm and its VLSI architecture
Field programmable gate array based parallel matrix multiplier for 3D affine transformations
Re-scalable V-BLAST MIMO system for FPGA
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- Author(s): G. Zhou and W.B. Mikhael
- Source: IEE Proceedings - Vision, Image and Signal Processing, Volume 153, Issue 6, p. 754 –760
- DOI: 10.1049/ip-vis:20050074
- Type: Article
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p.
754
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(7)
A novel adaptive discriminative vector quantisation technique for speaker identification (ADVQSI) is introduced. In the training mode of ADVQSI, for each speaker, the speech feature vector space is divided into a number of subspaces. The feature space segmentation is based on the difference between the probability distribution of the speech feature vectors from each speaker and that from all speakers in the speaker identification (SI) group. Then, an optimal discriminative weight, which represents the subspace's role in SI, is calculated for each subspace of each speaker by employing adaptive techniques. The largest template differences between speakers in the SI group are achieved by using optimal discriminative weights. In the testing mode of ADVQSI, discriminative weighted average vector quantisation (VQ) distortions are used for SI decisions. The performance of ADVQSI is analysed and tested experimentally. The experimental results confirm the performance improvement employing the proposed technique in comparison with existing VQ techniques for SI and recently reported discriminative VQ techniques for SI (DVQSI). - Author(s): S.-M. Tsai and J.-F. Yang
- Source: IEE Proceedings - Vision, Image and Signal Processing, Volume 153, Issue 6, p. 761 –768
- DOI: 10.1049/ip-vis:20060123
- Type: Article
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p.
761
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(8)
To reduce the computational complexity of algebraic code-excited linear prediction (ACELP) coders, an efficient codebook search mechanism based on a simplified correlation matrix (SCM) of the vocal impulse response is proposed. In the proposed approach, the statistical characteristics of the vocal impulse response are identified such that only a small proportion of the total number of correlation coefficients in the correlation matrix need be calculated before the ACELP search procedure is carried out. Furthermore, the proposed joint scheme, by combining the SCM method and a pulse position prediction scheme, not only decreases the arithmetic complexity in the pre-computing autocorrelation matrix but also reduces the number of pulse position combinations. The simulation and experimental results show that the proposed method provides an effective reduction in the computational load of the ACELP codebook search procedure with no discernible degradation of the speech quality. - Author(s): L. Wu ; P. Shi ; H. Gao ; C. Wang
- Source: IEE Proceedings - Vision, Image and Signal Processing, Volume 153, Issue 6, p. 769 –784
- DOI: 10.1049/ip-vis:20050372
- Type: Article
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p.
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The problem of ℋ∞ model reduction for two-dimensional (2-D) discrete systems with delay in state is considered. The mathematical model of 2-D systems is established on the basis of the well-known Fornasini–Marchesini local state-space. First, conditions are established to guarantee the asymptotic stability and a prescribed noise attenuation level in the ℋ∞ sense for the underlying system. For a given stable system, attention is focused on the construction of a reduced-order model, which approximates the original system well in an ℋ∞ norm sense. Sufficient conditions are proposed for the existence of admissible reduced-order solutions. Since these obtained conditions are not expressed as strict linear matrix inequalities (LMIs), the cone complementary linearisation method is exploited to cast them into sequential minimisation problems subject to LMI constraints, which can be readily solved using standard numerical software. These obtained results are further extended to more general cases whose system states contain multiple delays. Two numerical examples are provided to demonstrate the effectiveness of the proposed techniques. - Author(s): Y. Abe and Y. Iiguni
- Source: IEE Proceedings - Vision, Image and Signal Processing, Volume 153, Issue 6, p. 785 –794
- DOI: 10.1049/ip-vis:20050259
- Type: Article
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p.
785
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(10)
A periodic radial basis function (RBF) network based on the regularisation approach is proposed. The periodic RBF network can eliminate the Gibbs phenomenon observed in the conventional RBF network at the boundary of the data. For the evaluation of the interpolation capability, the frequency response of the periodic RBF network is analysed. It is then theoretically shown that the frequency response is asymptotically equivalent to the ideal sinc interpolation, and that the RBF interpolation is closer to the ideal sinc interpolation than the cubic spline and Lanczos interpolations. - Author(s): J.K. Wu ; Y. Liang ; Q. Wu ; G.T. Chen
- Source: IEE Proceedings - Vision, Image and Signal Processing, Volume 153, Issue 6, p. 795 –804
- DOI: 10.1049/ip-vis:20050148
- Type: Article
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p.
795
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(10)
A technique for tracking the frequency of power systems in sine noises using numerical differentiation is presented. A voltage or current sinusoidal signal corrupted by sine noises and white noises is considered. For the signal corrupted by one or two sine noises, a central numerical differentiation-based method is proposed. For the signal corrupted by multiple sine noises and white noises, a hybrid method of numerical differentiation and a digital finite impulse response (FIR) filter are proposed. The digital FIR filtering algorithm is used to remove the white noises and the sine noises, and the numerical differentiation algorithm is used to estimate the fundamental frequency of power systems when the fundamental component is decomposed out of the signal. The proposed algorithm shows an advantage in time and speed when compared with other existing techniques and shows better dynamics and higher accuracy in frequency estimation. Carried out in Matlab, the simulation results are satisfactory. - Author(s): C.-M. Lee ; S.-S. Yang ; C.-L. Ho
- Source: IEE Proceedings - Vision, Image and Signal Processing, Volume 153, Issue 6, p. 805 –809
- DOI: 10.1049/ip-vis:20050139
- Type: Article
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p.
805
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This study presents a modified back-propagation (BP) algorithm for a multilayer perceptron (MLP) to perfect its ability to cope with the problem of binary phase shift keying channel equalisation. For a typical BP algorithm, the error signal is obtained from the comparison between the target and estimated signal. The error signal is propagated layer by layer from the output layer to the input layer to adaptively adjust all weights in the MLP. Therefore all parameters of the MLP are obtained by a single BP algorithm. However, the structure of the MLP with a hidden layer provides the feasibility to modify the BP algorithm to improve its performance. The MLP can be divided from the hidden layer into two sub-MLPs, and each sub-MLP is optimised by its own BP algorithm. Accordingly, the whole MLP is adjusted by two BP algorithms independently. In this study, the modified BP algorithm is utilised to cope with the problem of channel equalisation. The simulation results show that the modified BP algorithm indeed improves the typical BP algorithm especially for an environment with nonlinear distortion, frequency offset, and phase and timing errors. Moreover, the computation complexity of the proposed algorithm almost equals that of the conventional BP algorithm. - Author(s): B.-Y. Wang and W.X. Zheng
- Source: IEE Proceedings - Vision, Image and Signal Processing, Volume 153, Issue 6, p. 810 –814
- DOI: 10.1049/ip-vis:20060009
- Type: Article
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p.
810
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In chaotic communications, an ideal channel is often assumed. In practice, channel distortion is inevitable. In particular, in wireless chaotic communications, the channel distortion may be serious and must be compensated. An adaptive blind equalisation algorithm is proposed. The aim of the algorithm is to recover the chaotic signal transmitted through a finite impulse response (FIR) channel. The inherent characteristic of the chaotic signal, that is the high sensitivity to initial conditions, is exploited to formulate the criterion used in deriving the algorithm. The analysis of stability of the proposed algorithm is also provided. - Author(s): S. Suchitra ; S.K. Lam ; C.T. Clarke ; T. Srikanthan
- Source: IEE Proceedings - Vision, Image and Signal Processing, Volume 153, Issue 6, p. 815 –824
- DOI: 10.1049/ip-vis:20050077
- Type: Article
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815
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Real-time image rotation is an essential operation in many application areas such as image processing, computer graphics and pattern recognition. Existing architectures that rely on CORDIC computations for trigonometric operations cause a severe bottleneck in high-throughput applications, especially where high-resolution images are involved. A novel hierarchical method that exploits the symmetrical characteristics of the image to accelerate the rotation of high-resolution images is presented. Investigations based on a 512×512 image show that the proposed method yields a speedup of ∼20× for a mere 3% increase in area cost when compared with existing techniques. Moreover, the effect of hierarchy on the computational efficiency has been evaluated to provide for area–time flexibility. The proposed technique is highly scalable and significant performance gains are evident for very high-resolution images. - Author(s): X. Zhang and S. Wang
- Source: IEE Proceedings - Vision, Image and Signal Processing, Volume 153, Issue 6, p. 825 –836
- DOI: 10.1049/ip-vis:20045200
- Type: Article
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p.
825
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Image restoration is formulated using a truncated singular-value-decomposition (SVD) filter bank. A pair of known data patterns is used for identifying a small convolution operator. This is achieved by matrix pseudo-inversion based on SVD. Unlike conventional approaches, however, here SVD is performed upon a data-pattern matrix that is much smaller than the image size, leading to an enormous saving in computation. Regularisation is realised by first decomposing the operator into a bank of sub-filters, and then discarding some high-order ones to avoid noise amplification. By estimating the noise spectrum, sub-filters that produce noise energy more than that of useful information are abandoned. Therefore high-order components in the spectrum responsible for noise amplification are rejected. With the obtained small kernel, image restoration is implemented by convolution in the space domain. Numerical results are given to show the effectiveness of the proposed technique. - Author(s): C.-I. Chang ; Y. Du ; J. Wang ; S.-M. Guo ; P.D. Thouin
- Source: IEE Proceedings - Vision, Image and Signal Processing, Volume 153, Issue 6, p. 837 –850
- DOI: 10.1049/ip-vis:20050032
- Type: Article
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p.
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Entropy-based image thresholding has received considerable interest in recent years. Two types of entropy are generally used as thresholding criteria: Shannon's entropy and relative entropy, also known as Kullback–Leibler information distance, where the former measures uncertainty in an information source with an optimal threshold obtained by maximising Shannon's entropy, whereas the latter measures the information discrepancy between two different sources with an optimal threshold obtained by minimising relative entropy. Many thresholding methods have been developed for both criteria and reported in the literature. These two entropy-based thresholding criteria have been investigated and the relationship among entropy and relative entropy thresholding methods has been explored. In particular, a survey and comparative analysis is conducted among several widely used methods that include Pun and Kapur's maximum entropy, Kittler and Illingworth's minimum error thresholding, Pal and Pal's entropy thresholding and Chang et al.'s relative entropy thresholding methods. In order to objectively assess these methods, two measures, uniformity and shape, are used for performance evaluation. - Author(s): Q. Zhou and J.P. Oakley
- Source: IEE Proceedings - Vision, Image and Signal Processing, Volume 153, Issue 6, p. 851 –859
- DOI: 10.1049/ip-vis:20060016
- Type: Article
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p.
851
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A multiscale product filter (MSPF) structure is proposed for use in digital image enhancement. The objective for this type of image processing is to mitigate the effect of uneven illumination on perceived image quality, a process known as dynamic range compression (DRC). The properties of the MSPF for DRC are investigated, a theoretical model is presented, and this model is used to predict the performance of the filter under step changes in illumination such as those caused by shadows. The advantage of the MSPF is that it provides a relatively rapid response for transitions from shadow regions to well-lit regions. This property is verified using random Mondrian textures with simulated illumination changes. The estimated illumination profile is compared with that used to generate the synthetic image using the Pearson's correlation coefficient. The improved performance of the MSPF is also confirmed by the mitigation of shadow artefacts in real images. - Author(s): A. Molino ; F. Vacca ; G. Masera ; T.Q. Nguyen
- Source: IEE Proceedings - Vision, Image and Signal Processing, Volume 153, Issue 6, p. 860 –868
- DOI: 10.1049/ip-vis:20060011
- Type: Article
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p.
860
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To efficiently compute the phase difference (PD) between two complex numbers, two novel approaches are described. The problem of fast PD computation is central in many applications. As a case study, the main focus is on the phase correlation technique that is used for motion estimation. Starting from the problem statement, the system requirements are dealt with showing how PD requires a remarkable amount of computational resources. Reduced complexity techniques are then proposed and specifically tailored to suit the application needs. Each solution is completely implemented both in 0.25 µm as well as 0.13 µm CMOS. The so-called LUT-ROT exhibits noteworthy figures in terms of area occupation, delay and power dissipation, saving nearly 50% in terms of area and power when compared to recent work on this subject. - Author(s): J. Díaz ; E. Ros ; S. Mota ; F. Pelayo ; E.M. Ortigosa
- Source: IEE Proceedings - Vision, Image and Signal Processing, Volume 153, Issue 6, p. 869 –880
- DOI: 10.1049/ip-vis:20050207
- Type: Article
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p.
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A pipelined optical-flow processing system that works as a virtual motion sensor has been described. It is based on a field programmable gate array (FPGA) device enabling the easy change of configuring parameters to adapt the sensor to different speeds, light conditions and other environmental factors. It is referred to as a ‘virtual sensor’ because it consists of a conventional camera as front-end supported by an FPGA processing device, which embeds the frame grabber, optical-flow algorithm implementation, output module and some configuration and storage circuitry. This is the first fully stand-alone working optical-flow processing system to include both accuracy and speed of measurement of the platform performance. The customisability of the system for different hardware resources and platforms has also been discussed, showing the resources and performance for a stand-alone board and a PCI co-processing board. - Author(s): H. Fu and Z. Chi
- Source: IEE Proceedings - Vision, Image and Signal Processing, Volume 153, Issue 6, p. 881 –892
- DOI: 10.1049/ip-vis:20060061
- Type: Article
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p.
881
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Living plant recognition based on images of leaf, flower and fruit is a very challenging task in the field of pattern recognition and computer vision. There has been little work reported on flower and fruit image processing and recognition. In recent years, several researchers have dedicated their work to leaf characterisation. As an inherent trait, leaf vein definitely contains the important information for plant species recognition despite its complex modality. A new approach that combines a thresholding method and an artificial neural network (ANN) classifier is proposed to extract leaf veins. A preliminary segmentation based on the intensity histogram of leaf images is first carried out to coarsely determine vein regions. This is followed by a fine segmentation using a trained ANN classifier with ten features extracted from a window centred on the object pixel as its inputs. Compared with other methods, experimental results show that this combined approach is capable of extracting more accurate venation modality of the leaf for the subsequent vein pattern classification. The approach can also reduce the computing time compared with a direct neural network approach.
Speaker identification based on adaptive discriminative vector quantisation
Efficient algebraic code-excited linear predictive codebook search
ℋ∞ mode reduction for two-dimensional discrete state-delayed systems
Interpolation capability of the periodic radial basis function network
Frequency tracking techniques of power systems in coloured noises
Modified back-propagation algorithm applied to decision-feedback equalisation
Adaptive blind channel equalisation in chaotic communications by using nonlinear prediction technique
Accelerating rotation of high-resolution images
Image restoration using truncated SVD filter bank based on an energy criterion
Survey and comparative analysis of entropy and relative entropy thresholding techniques
Advantages of multiscale product filters for dynamic range compression in images
Scalable phase extraction methods for phase plane motion estimation
Subpixel motion computing architecture
Combined thresholding and neural network approach for vein pattern extraction from leaf images
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