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Frequency-domain weighted-least-squares design of quadratic interpolators

IET SIGNAL processing 2010年第1期4卷 102-111页

作者： Deng, T. -B. Toho Univ Dept Informat Sci Fac Sci Chiba 2748510 Japan

Existing finite-support interpolators are derived from continuities in the time-domain. In this study, the authors optimally design a quadratic interpolator using two second-degree piecewise polynomials in the frequency-domain. The optimal coefficients of the piecewise polynomials are found by minimising the weighted least-squares error between the ideal and actual frequency responses of the quadratic interpolator subject to a few constraints. Adjusting the weighting functions in different frequency bands can yield accurate frequency response in a specified passband and even can ignore 'don't care' bands so that various quadratic interpolators can be designed for interpolating various discrete signals containing different frequency components. One-dimensional and two-dimensional examples have shown that the quadratic interpolator can achieve much higher interpolation accuracy than the existing interpolators for wide-band signals, and various images have been tested to verify that the quadratic interpolator can achieve comparable interpolation accuracy as the Catmull-Rom cubic for narrow-band signals (images), but the computational complexity can be reduced to about 70%. Therefore both narrow-band and wide-band signals can be interpolated with high accuracy.

关键词： piecewise polynomials computer vision and image processing techniques interpolation wideband signals frequency-domain weighted-least-squares design quadratic interpolators Interpolation and function approximation (numerical analysis) second-degree piecewise polynomials computational complexity Optical, image and video signal processing least squares approximations discrete signals finite-support interpolators image processing Catmull-Rom cubic

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Algorithm to decompose three-dimensional complex structures at the necks: tested on snow structures

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IET image processing 2011年第2期5卷 132-140页

作者： Theile, T. Schneebeli, M. WSL Inst Snow & Avalanche Res SLF CH-7260 Davos Switzerland

The separation of overlapping particles in three-dimensional images is an image processing task with many fields of application. However, commonly used image processing algorithms have difficulties to identify the single particles and their connections in certain structures. Here the authors present an alternative algorithm for part decomposition, which performs better on some structures than common algorithms. This algorithm is a special case of part decomposition, as it decomposes a structure at the necks into single particles. The necks are detected based on their characteristic negative Gaussian curvature. The algorithm itself consists of three steps: cutting at negative Gaussian curvature, region growing and intersecting plane minimisation. The authors tested the performance of the algorithm by comparison with two state-of-the-art algorithms for part decomposition, the watershed and a skeleton-based algorithm on strongly differing geometries, taken from natural snow samples. The two test algorithms are known for having difficulties to decompose certain structures. As the new algorithm uses a different characteristic to decompose the structure, the new algorithm is a good alternative to the existing algorithms. The new algorithm decomposes 72% of the reference structure correctly. This is a better performance than by the two other algorithms.

关键词： snow structures structural engineering computing Mechanical engineering applications of IT three-dimensional images image processing snow negative Gaussian curvature computer vision and image processing techniques decompose three-dimensional complex structures Mechanical structures skeleton-based algorithm Optical, image and video signal processing Civil and mechanical engineering computing overlapping particles

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Mathernatical-morphology-based edge detectors for detection of thin edges in low-contrast regions

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IET image processing 2007年第3期1卷 269-277页

作者： Jiang, J.-A. Chuang, C.-L. Lu, Y.-L. Fahn, C.-S. Natl Taiwan Univ Dept Bioind Mechatron Engn Taipei 106 Taiwan Natl Taiwan Univ Sci & Technol Dept Comp Sci & Informat Engn Taipei 106 Taiwan Natl Taiwan Univ Inst Biomed Engn Taipei 106 Taiwan

A new edge detector based on mathematical morphology to preserve thin edge features in low-contrast regions as well as other apparent edges is proposed. A quad-decomposition edge enhancement process, a thresholding process, and a mask-based noise filtering process were developed and used to enhance thin edge features, extract edge points and filter out some meaningless noise points, respectively. Moreover, five bipolar oriented edge masks were also designed to remove most of the incorrectly detected edge features. Many experiments were conducted to evaluate and compare the performance of the proposed algorithm and several conventional ones. Pratt's figure of merit achieved by the proposed algorithm was as high as 92.5. The comprehensive experimental results show that the proposed algorithm is capable of preserving thin edge details successfully in low-contrast regions and is robust against noise.

关键词： filtering theory edge detection computer vision and image processing techniques mask-based noise filtering process quad-decomposition edge enhancement process mathematical-morphology-based edge detector Pratt figure mathematical morphology bipolar oriented edge mask Filtering methods in signal processing image enhancement low-contrast region thresholding process Optical, image and video signal processing image segmentation

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Social graph convolutional LSTM for pedestrian trajectory prediction

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IET INTELLIGENT TRANSPORT SYSTEMS 2021年第3期15卷 396-405页

作者： Zhou, Yutao Wu, Huayi Cheng, Hongquan Qi, Kunlun Hu, Kai Kang, Chaogui Zheng, Jie Wuhan Univ State Key Lab Informat Engn Surveying Mapping & R Wuhan 430079 Peoples R China Wuhan Univ Sch Remote Sensing & Informat Engn Wuhan Peoples R China China Univ Geosci Wuhan Sch Geog & Informat Engn Wuhan Peoples R China Jiangnan Univ Sch Internet Things Wuxi Peoples R China NYU Ctr Urban Sci Progress Brooklyn NY USA

Understanding the movement of pedestrians and predicting their future trajectory can be very important in intelligent transportation systems because accurate pedestrian trajectory prediction will improve the level of autonomous driving technology and reduce traffic accidents. The authors address this problem with a social graph convolutional long short-term memory neural network architecture by considering the movement information of each pedestrian and its interaction with neighbours. Specifically, the authors use a graph to model pedestrian walking state where nodes denote the pedestrian movement information, and edges represent the interactions between pairwise pedestrians. An end-to-end architecture that combines a sequence-to-sequence model with a graph convolutional network to learn the movement features and interaction features is used. To capture the interaction influence on different pedestrians, an emotion gate to refine the learned features and filter out useless information is introduced. A companion loss function to increase the ability of the network to capture 'walking in groups' behaviour is further proposed. Through experiments on two public datasets (ETH and UCY), the authors prove that our method outperforms the previous methods.

关键词： computer vision and image processing techniques Traffic engineering computing Other topics in statistics Combinatorial mathematics

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Finger vein recognition algorithm under reduced field of view

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IET image processing 2021年第4期15卷 947-955页

作者： Jin, Jian Di, Si Li, Weijian Sun, Xuetong Wang, Xudi Hefei Univ Technol Sch Mech & Automot Engn Hefei Anhui Peoples R China Chinese Acad Sci Guangzhou Inst Adv Technol 1121 Haibin Rd Guangzhou Peoples R China Chinese Acad Sci Shenzhen Inst Adv Technol Shenzhen Peoples R China Chengdu Univ Technol Coll Informat Sci & Technol Chengdu Peoples R China

Algorithms for finger vein recognition methods are generally designed based on greyscale images containing vein distributions, but greyscale inhomogeneities and non-venous texture structures often adversely affect the recognition results. Besides, the performance of the algorithm when the field of view is reduced has not been studied. Therefore, the aim of this paper is to propose an algorithm based on binary image, so as to minimize the interference of non-venous factors in the identification process. We use the feature from accelerated segment test algorithm to detect feature points, and use gradient histogram to describe these feature points in a vectorized manner. In addition, we propose the concept of circular matching neighbourhood, and select the matching feature point pairs in this area. Then, the Euclidean distance and the number of correct matching pairs were comprehensively considered to increase the recognition rate of the algorithm. The algorithm was tested on the database of SDU-MLA, FV-USM and MMCBNU-6000. The results show that the algorithm has certain advantages before and after the field of view is reduced. Therefore, this paper not only provides a new idea for finger vein recognition, but also has practical application value for the miniaturization of finger vein acquisition devices.

关键词： Optical, image and video signal processing image recognition computer vision and image processing techniques

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Accuracy and numerical stability of high-order polar harmonic transforms

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IET image processing 2012年第6期6卷 617-626页

作者： Singh, C. Upneja, R. Punjabi Univ Dept Comp Sci Patiala Punjab India

Invariant moments and transforms are a special kind of statistical measure designed to remain constant after some transformations, such as object rotation, scaling, translation or image illumination changes, in order to improve the reliability of a pattern recognition system. Polar harmonic transforms (PHTs) are one of such image descriptors based on a set of orthogonal projection bases, which are better rated in comparison with other moments and transforms because they possess less redundant information. PHTs suffer from geometric error and numerical integration error. Geometric error is caused when a square image is mapped into a unit circular disk, which cannot exactly match the square domain. Numerical integration error is caused when the integration is approximated by zeroth-order summation. We propose a computational framework based on numerical integration approach that reduces the geometric error and the numerical integration error simultaneously. The effect of the improved accuracy in the PHTs is analysed for rotation invariance, scale invariance and image noise. Various numerical experiments demonstrate that the effect of these errors is much more prominent in small images and, therefore the proposed method is suitable for applications involving small images, such as in optical character recognition and template-matching applications.

关键词： integration numerical integration error statistical analysis optical character recognition scale invariance PHT statistical measure unit circular disk computer vision and image processing techniques image processing template-matching invariant moment geometric error object rotation zeroth-order summation Optical, image and video signal processing Integral transforms numerical stability Numerical integration and differentiation image noise pattern recognition Integral transforms in numerical analysis object scaling image illumination transforms orthogonal projection bases rotation invariance high-order polar harmonic transform image descriptor

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Multi-focus image fusion evaluation based on jointly sparse representation and atom focus measure

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IET image processing 2021年第5期15卷 1032-1041页

作者： Hu, Yanxiang Zhang, Bo Zhang, Juntong Gao, Qian Tianjin Normal Univ Coll Comp & Informat Engn Tianjin Peoples R China

Multi-focus image fusion (MFIF) tries to combine images with different in-focus regions and get a composite image that is in focus everywhere. Although many new MFIF algorithms based on various new representation models have been proposed in recent years, the performance evaluation of MFIF is still a challenging issue. In this study, a novel MFIF objective evaluation metric based on jointly sparse representation and atom focus measure is proposed. It not only provides a more reliable alternative for MFIF quality measurement but also supplies a unique MFIF performance analysis method at the same time. In the measurement, the sources and their fusion results are decomposed jointly sparse with an over-complete learning dictionary to extract the atom remnants of the source images. Meanwhile, in order to emphasise the fusion effect of in-focus atoms, the sum-modified-Laplacian model is used to measure the atom focus degree. Then, the atom remnants weighted by their focus measures are used to measure MFIF quality. In the experiments, nine recently proposed fusion algorithms were tested to contrast the proposed metrics with other four widely used objective metrics. The experimental results demonstrated the rationality and accuracy of our method. Moreover, it was also proved quantificationally that the fusion degree of atoms is directly related to their in-focus degree, the high in-focus degree atoms usually have poor fusion effect.

关键词： Optical, image and video signal processing Sensor fusion computer vision and image processing techniques

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Robust watermarking using fractional wavelet packet transform

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IET image processing 2012年第4期6卷 386-397页

作者： Bhatnagar, G. Raman, B. Wu, Q. M. J. Univ Windsor Dept Elect & Comp Engn Windsor ON N9B 3P4 Canada Indian Inst Technol Dept Math Roorkee Uttar Pradesh India

In this study, the concept of fractional wavelet packet transform is explored with its application in digital watermarking. The core idea of the proposed watermarking scheme is to decompose an image via fractional wavelet packet transform and then a reference image is created by changing the positions of all frequency sub-bands at each level with respect to some rule which is secret and only known to the owner/creator. For embedding, the reference image is segmented into non-overlapping blocks and modify its singular values with the watermark singular values. Finally, a reliable watermark extraction algorithm is developed for the extraction of watermark from the distorted image. The feasibility of this method and its robustness against different kind of attacks are verified by computer simulations.

关键词： computer vision and image processing techniques image watermarking image and video coding fractional wavelet packet transform digital watermarking Data security wavelet transforms watermark extraction algorithm Integral transforms image segmentation

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Local binary pattern and its derivatives for face recognition

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IET computer vision 2012年第5期6卷 480-488页

作者： Suruliandi, A. Meena, K. Rose, R. Reena Manonmaniam Sundaranar Univ Dept Comp Sci & Engn Tirunelveli Tamil Nadu India Sardar Raja Coll Engn Dept Comp Sci & Engn Tirunelveli 627808 Tamil Nadu India St Xaviers Catholic Engn Coll Dept Comp Sci & Engn Kanyakumari Tamil Nadu India

Texture is the surface property that is used to identify and recognise objects. This property is widely used in many applications including texture-based face recognition systems, surveillance, identity verification and so on. The Local binary pattern (LBP) texture method is most successful for face recognition. Owing to the great success of LBP, recently many models, which are variants of LBP have been proposed for texture analysis. Some of the derivatives of LBPs are multivariate local binary pattern, centre symmetric local binary pattern, local binary pattern variance, dominant local binary pattern, advanced local binary pattern, local texture pattern (LTP) and local derivative pattern (LDP). In this scenario, it is essential to review, whether LBP or their derivatives perform better for face recognition. The real-time challenges such as illumination changes, rotations, angle variations and facial expression variations are evaluated by different LBP-based models. Experiments were conducted on the Japanese female facial expression, YALE and FRGC version2 databases. The results show that LDP and LTP perform much better than the other LBP-based models.

关键词： multivariate local binary pattern YALE databases advanced local binary pattern face recognition systems LBP-based models angle variations image recognition LDP Spatial and pictorial databases visual databases facial expression variations centre symmetric local binary pattern local derivative pattern surveillance face recognition local binary pattern texture method surface property illumination changes computer vision and image processing techniques Japanese female facial expression FRGC version2 databases image texture local binary pattern variance identity verification dominant local binary pattern

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Balancing performance factors in multisource biometric processing platforms

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IET SIGNAL processing 2009年第4期3卷 342-351页

作者： Fairhurst, M. C. Abreu, M. C. C. Univ Kent Dept Elect Canterbury CT2 7NT Kent England

It is generally recognised that no one biometric data source or processing platform is universally appropriate for optimising performance across all problem domains. Multibiometric processors, which combine identity information obtained from more than one biometric source are commonly promoted as optimal structures for maximising performance, and much research has been carried out to investigate appropriate strategies for combining the available information. However, the techniques of multiclassifier pattern recognition also offer opportunities to improve the performance of systems operating within a unimodal environment, yet such solutions have been less extensively investigated in the specific case of biometric applications. This study presents an empirical study of the relations between these two different approaches to enhancing the performance indicators delivered by biometric systems. In particular we are interested to increase our understanding of the relative merits of, on the one hand, multiclassifier/single modality systems and, on the other, full multibiometric configurations. We focus our study on three modalities, the fingerprint and hand geometry (two physiological biometrics) and the handwritten signature (a behavioural biometric).

关键词： computer vision and image processing techniques fingerprint identification handwriting recognition handwritten signature biometric data source hand geometry multiclassifier pattern recognition image recognition performance indicators handwritten character recognition multisource biometric processing platforms fingerprint geometry single modality systems

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