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image-based facial recognition in the domain of high-order polynomial one-way mapping

IET image processing 2008年第3期2卷 139-149页

作者： Dabbah, M. A. Woo, W. L. Dlay, S. S. Newcastle Univ Newcastle Upon Tyne NE1 7RU Tyne & Wear England

The authors present a secure facial recognition system. The biometric data are transformed to the cancellable domain using high-order polynomial functions and co-occurrence matrices. The proposed method has provided both high-recognition accuracy and biometric data protection. Protection of data relies on the polynomial functions, where the new reissued cancellable biometric can be obtained by changing the polynomial parameters. Besides the protection of data, the reconstructed co-occurrence matrices also contributed to the accuracy enhancement. Hadamard product is used to reconstruct the new measure and has shown high flexibility in proving a new relationship between two independent covariance matrices. The proposed cancellable biometric is treated in the same manner as the original biometric data, which enables replacement of original data by the novel cancellable algorithm with no change to the authentication system. The two-dimensional principal component analysis recognition algorithm is used at the authentication stage. Results have shown high non-reversibility of data with improved accuracy over the original data and raised the performance recognition rate to 97%.

关键词： Hadamard product Algebra two-dimensional principal component analysis cooccurrence matrices image recognition face recognition computer vision and image processing techniques covariance matrices high-order polynomial one-way mapping principal component analysis biometric data protection Interpolation and function approximation (numerical analysis) high-order polynomial functions polynomials Other topics in statistics image-based facial recognition high-recognition accuracy biometrics (access control)

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Real-time pedestrian classification exploiting 2D and 3D information

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IET INTELLIGENT TRANSPORT SYSTEMS 2008年第3期2卷 201-210页

作者： Corneliu, T. Nedevschi, S. Tech Univ Cluj Napoca Dept Comp Sci Cluj Napoca 400020 Romania

A new approach for standing and walking pedestrian detection using pattern matching and exploiting both 2D image information and 3D dense stereo information is proposed. Because 3D information accuracy does not allow the direct classification of the 3D shape, a combined 3D-2D method is proposed. The 3D data are used in an innovative way for pedestrian hypotheses generation, scale and depth estimation and 2D models selection. Also the 3D hypotheses allow the corresponding 2D image region of interest selection and the 2D hypothesis generation. The 2D hypothesis consists of the object's external edges obtained by an edge extraction and a depth coherency-based filtering out process. The scaled models are matched against the selected hypothesis using an elastic high-speed matching based on the Chamfer distance. The method has been tested on synthetic and real-world scenarios.

关键词： edge detection image recognition 3D dense stereo information real-time pedestrian classification pattern matching computer vision and image processing techniques 3D information Chamfer distance stereo image processing depth coherency-based filtering elastic high-speed matching filtering theory 2D information edge extraction pedestrian detection

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Efficient algorithm for very low bit rate embedded image coding

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IET image processing 2008年第2期2卷 59-71页

作者： Moinuddin, A. A. Khan, E. Ghanbari, M. Aligarh Muslim Univ Dept Elect Engn Aligarh Uttar Pradesh India Univ Essex Dept Comp & Elect Syst Colchester CO4 3SQ Essex England

The authors propose an embedded wavelet-based image coding algorithm that exploits both the inter- and intra-subband correlations among the wavelet coefficients. The proposed coding algorithm is based on spatial orientation trees (SOT) in which the basic unit is a block of m x n coefficients in contrast to a single coefficient in the set partitioning in hierarchical trees (SPIHT) algorithm. Each SOT has a root node (a block of m x n coefficients) in the LL-subband with the child and descendent blocks in the high frequency subbands. Thus it fuses the features of both block- and tree-based coding algorithms into a single algorithm. Performance of the proposed method is compared (in terms of rate-distortion performance) with the other state-of-the-art coding algorithms including the JPEG2000 for popular test images. Simulation results show that the proposed algorithm has a better coding efficiency over the other coders at very low bit rates. Also, compared with SPIHT it reduces the elements of the auxiliary lists, thereby reducing the memory requirements. In addition, the encoder of the proposed algorithm is significantly faster than that of the SPIHT, but with a slight increase in its decoder complexity.

关键词： low bit rate embedded image coding set partitioning computer vision and image processing techniques data encapsulation image and video coding image coding wavelet transforms hierarchical tree algorithm Combinatorial mathematics Integral transforms spatial orientation tree decoding trees (mathematics)

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Video texture modelling and synthesis using fractal processes

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IET image processing 2008年第1期2卷 1-17页

作者： Campisi, P. Maiorana, E. Neri, A. Scarano, G. Univ Rome Ter Dip Elettr Appl I-00146 Rome Italy Univ Roma La Sapienza Dip INFOCOM I-00184 Rome Italy

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 (313) 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.

关键词： Fourier analysis fractional Brownian motion process estimation theory video signal processing computer vision and image processing techniques Optical, image and video signal processing Mathematical analysis incremental Fourier synthesis algorithm video texture synthesis autocorrelation function estimation 3D ESS model image texture Video signal processing correlation methods extended self-similar model Graphics techniques Brownian motion solid modelling Other topics in statistics fractal-based approach video texture modelling fractals

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Design of frequency-coded waveforms for target detection

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IET RADAR SONAR AND NAVIGATION 2008年第5期2卷 388-394页

作者： Bhatt, T. D. Rajan, E. G. Rao, P. V. D. Somasekhar MGIT Dept ECE Hyderabad Andhra Pradesh India Pentagram Res Ctr P Ltd Hyderabad Andhra Pradesh India JNT Univ Acad Staff Coll Hyderabad Andhra Pradesh India

The authors propose a novel approach to the design of frequency-coded waveforms using modified pushing sequences. The resulting waveforms show that there is considerable enhancement in delay-Doppler resolution in the ... 详细信息

关键词： delay-Doppler resolution computer vision and image processing techniques target detection Doppler shift object detection Optical, image and video signal processing frequency-coded waveforms image enhancement image resolution modified pushing sequences

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Wavelet-based image denoising with the normal inverse Gaussian prior and linear MMSE estimator

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IET image processing 2008年第4期2卷 203-217页

作者： Bhuiyan, M. I. H. Ahmad, M. O. Swamy, M. N. S. Concordia Univ Dept Elect & Comp Engn Ctr Commun & Signal Proc Montreal PQ H3G 1M8 Canada

A new spatially adaptive wavelet-based method is introduced for reducing noise in images corrupted by additive white Gaussian noise. It is shown that a symmetric normal inverse Gaussian distribution is highly suitable for modelling the wavelet coefficients. In order to estimate the parameters of the distribution, a maximum-likelihood-based technique is proposed, wherein the Gauss-Hermite quadrature approximation is exploited to perform the maximisation in a computationally efficient way. A Bayesian minimum mean-squared error (MMSE) estimator is developed utilising the proposed distribution. The variances corresponding to the noise-free coefficients are obtained from the Bayesian estimates using a local neighbourhood. A modified linear MMSE estimator that incorporates both intra-scale and inter-scale dependencies is proposed. The performance of the proposed method is studied using typical noise-free images corrupted with simulated noise and compared with that of the other state-of-the-art methods. It is shown that the proposed method gives higher values of the peak signal-to-noise ratio compared with most of the other denoising techniques and provides images of good visual quality. Also, the performance of the proposed method is quite close to that of the state-of-the-art Gaussian scale mixture (GSM) method, but with much less complexity.

关键词： Bayesian minimum mean-squared error estimator Bayesian estimates adaptive estimation maximisation symmetric normal inverse Gaussian distribution adaptive wavelet-based method noise-free coefficients normal inverse Gaussian prior Gaussian scale mixture computer vision and image processing techniques Other topics in statistics linear MMSE estimator noise-free images Optical, image and video signal processing Mathematical analysis Integral transforms visual quality Gauss-Hermite quadrature approximation maximum likelihood estimation signal-to-noise ratio Bayes methods Gaussian distribution wavelet coefficients wavelet transforms Interpolation and function approximation (numerical analysis) parameter estimation inverse problems maximum-likelihood-based technique image denoising computational complexity additive white Gaussian noise least mean squares methods wavelet-based image denoising

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Fast centre-surround contrast modification

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IET image processing 2008年第1期2卷 19-34页

作者： Vonikakis, V. Andreadis, I. Gasteratos, A. Democritus Univ Thrace Dept Elect & Comp Engn Elect Lab Sect Elect & Informat Syst Technol GR-67100 Xanthi Greece Democritus Univ Thrace Lab Robot & Automat Sect Prod Syst Dept Prod & Management GR-67100 Xanthi Greece

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 x 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.

关键词： image resolution multiscale Retinex colour rendition standard dynamic range images automatic colour equalisation computer vision and image processing techniques image processing algorithms conventional personal computer centre-surround contrast modification Optical, image and video signal processing image enhancement image colour analysis rational mapping function

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Discrete image modelling for piecewise constant segmentation by artificial neural networks

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IET image processing 2008年第1期2卷 37-47页

作者： De Santis, A. Iacoviello, D. Univ Roma La Sapienza Dipartimento Informat & Sistemist Antoniio Rubert I-00185 Rome Italy

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.

关键词： File organisation Neural computing techniques data representation computer vision and image processing techniques artificial neural network data structures approximation theory discrete image model Interpolation and function approximation (numerical analysis) piecewise constant segmentation neural nets Optical, image and video signal processing image segmentation image best approximation

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Flattest histogram specification with accurate brightness preservation

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IET image processing 2008年第5期2卷 249-262页

作者： Wang, C. Peng, J. Ye, Z. Univ Sci & Technol China Dept Elect Engn & Informat Sci Inst Stat Signal Proc Hefei 230027 Anhui Peoples R China

Brightness preservation is in great demand in the consumer electronics field, when the image is effectively enhanced. Finding the. attest target histogram for contrast enhancement subject to a constrained mean brightness is proposed. After that an exact histogram specification method is employed to help meet perfect brightness preservation. The authors name such a method as. attest histogram specification with accurate brightness preservation (FHSABP). Comparing with the existing methods, experiments show that FHSABP can not only enhance the image effectively, but also preserve the brightness quite well, and so it is possible for it to be utilised in consumer electronic products.

关键词： probability computer vision and image processing techniques accurate brightness preservation probability density function consumer electronics Optical, image and video signal processing flattest target histogram specification image enhancement Other topics in statistics consumer electronics field

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Fractal indexing with the joint statistical properties and its application in texture image retrieval

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IET image processing 2008年第4期2卷 218-230页

作者： Pi, M. Li, H. Univ Alberta Dept Comp Sci Edmonton AB T6G 2E8 Canada Univ Lethbridge Dept Math & Comp Sci Lethbridge AB T1K 3M4 Canada

Fractal image coding is a block-based scheme that exploits the self-similarity hiding within an image. Fractal parameters generated by the block-based scheme are quantitative measurements of self-similarity, and therefore they can be used to construct image signatures. By combining fractal parameters and collage error, a set of new statistical fractal signatures, such as histogram of collage error (HE), joint histogram of contrast scaling and collage error (JHSE), and joint histogram of range block mean and contrast scaling and collage error (JHMSE) is proposed. These fractal signatures effectively extract and reflect the statistical properties intrinsic in texture images. Hence, they provide new statistical features for use in texture image retrieval and identification. Furthermore, in order to reduce computational complexity of the JHMSE signature, the JHMSE signature is simplified to HM (histogram of range block mean) +JHSE and HM + HS (histogram of contrast scaling) +HE, based on the independence and distance equivalence. Mathematical analysis of the simplification scheme is also carried out. The proposed fractal signatures are compared with the existing fractal signatures. Experimental results show that the proposed signatures, HM + JHSE and HM + HS + HE, achieve a higher retrieval rate with a lower computational complexity.

关键词： indexing joint histogram of contrast scaling and collage error contrast scaling histogram range block mean histogram image signatures statistical analysis computer vision and image processing techniques texture image retrieval Other topics in statistics fractal indexing Information retrieval techniques image texture JHSE joint statistical properties image retrieval fractal image coding self-similarity hiding block-based scheme

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