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Robust vehicle tracking algorithm for nighttime videos captured by fixed cameras in highly reflective environments

IET COMPUTER VISION 2014年第6期8卷 535-544页

作者： Hajimolahoseini, Habib Amirfattahi, Rassoul Soltanian-Zadeh, Hamid Isfahan Univ Technol Dept Elect & Comp Engn Digital Signal Proc Res Lab Esfahan Iran Univ Tehran Sch Elect & Comp Engn CIPCE Tehran 14395515 Iran Henry Ford Hosp Dept Radiol Image Anal Lab Detroit MI 48202 USA

In this study, the problem of vehicle detection, tracking and speed estimation in the nighttime traffic surveillance videos captured in highly reflective environments is considered. In this case, a robust algorithm is proposed which uses vehicle headlights as their prominent features. The proposed algorithm consists of three main stages. In the first stage, bright objects are segmented by thresholding the grey-scale image. An effective algorithm is then applied to distinguish between vehicles lights and lights reflected on the road and on the vehicles bodies. In the second stage, the segmented bright objects are tracked using their spatial characteristics and their shapes and then, their speeds are estimated. To correct the camera perspective effect and reduce computational complexity, a projective transformation is used. In the third stage, the lights of each vehicle are grouped and paired using their positions and speeds. Motorbikes are also identified among the unpaired lights in this stage. Finally, the proposed real-time system is implemented in C and applied to videos captured by traffic surveillance cameras in some highways in Iran. Experimental results reveal that accuracy of the algorithm proposed for vehicle detection is more than 98%.

关键词： object detection object tracking video surveillance cameras road vehicles image segmentation computational complexity traffic engineering computing robust vehicle tracking algorithm fixed cameras highly reflective environments vehicle detection speed estimation nighttime traffic surveillance videos vehicle headlights bright object segmentation grey-scale image thresholding spatial characteristics camera perspective effect computational complexity reduction projective transformation traffic surveillance cameras Iran

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Alternative approach to calculate the structure matrix of Boolean network with semi-tensor product

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IET CONTROL THEORY AND APPLICATIONS 2017年第13期11卷 2048-2057页

作者： Zhang, Xiao Hua Han, Hua Xiang Sun, Zhi Jian Zhang, Wei Dong Shanghai Jiao Tong Univ Dept Automat Shanghai 200240 Peoples R China North China Univ Water Resources & Elect Power Sch Informat Engn Zhengzhou 450045 Henan Peoples R China

The structure matrix with semi-tensor product provides a basic tool for analysing the characteristics of Boolean networks (BNs). Directly calculating the structure matrix of BNs is very complex and requires considerable computational work. To overcome the drawbacks of the conventional method, this study gives an alternative way to obtain the network structure matrix through a series of matrix transformations. The key of the proposed new method is applying the superposition and expansion techniques to the initial matrix and the target matrix, which dramatically reduces computational complexity. An example is given to analyse the structure of the BN, and demonstrate the effectiveness of the proposed approach.

关键词： Boolean functions matrix algebra tensors computational complexity alternative approach structure matrix calculation Boolean network semitensor product BN matrix transformations superposition techniques expansion techniques initial matrix target matrix computational complexity reduction

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Set-Membership Type-1 Fuzzy Logic System Applied to Fault Classification in a Switch Machine

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IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 2017年第10期18卷 2703-2712页

作者： de Aguiar, Eduardo P. Nogueira, Fernando M. de A. Vellasco, Marley M. B. R. Ribeiro, Moises V. Univ Fed Juiz de Fora Ind & Mech Engn Dept Elect Engn Postgrad Program BR-36036330 Juiz De Fora MG Brazil Smarti9 Ltd BR-36036330 Juiz De Fora MG Brazil Pontifical Catholic Univ Rio de Janeiro Dept Elect Engn BR-22451900 Rio De Janeiro RJ Brazil

This paper focuses on the classification of faults in an electromechanical switch machine, which is an equipment used for handling railroad switches. In this paper, we introduce the use of Set-Membership concept, derived from the adaptive filter theory, into the training procedure of type-1 and singleton/non-singleton fuzzy logic systems, in order to reduce computational complexity and to increase convergence speed. We also present different criteria for using along with Set-Membership. Furthermore, we discuss the usefulness of delta rule delta, local Lipschitz estimation, variable step size, and variable step size adaptive techniques to yield additional improvement in terms of computational complexity reduction and convergence speed. Based on data set provided by a Brazilian railway company, which covers the four possible faults in a switch machine, we present performance analysis in terms of classification ratio, convergence speed, and computational complexity reduction. The reported results show that the proposed models result in improved convergence speed, slightly higher classification ratio, and remarkable computation complexity reduction when we limit the number of epochs for training, which may be required due to real-time constraint or low computational resource availability.

关键词： Fuzzy logic systems set-membership computational complexity reduction adaptive algorithms

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A reduced-complexity image coding scheme using decision-directed wavelet-based contourlet transform

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JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION 2012年第7期23卷 1128-1143页

作者： Hung, Chao-Hsiung Hang, Hsueh-Ming Natl Chiao Tung Univ Dept Elect Engn Hsinchu Taiwan

Recently the wavelet-based contourlet transform (WBCT) is adopted for image coding because it matches better image textures of different orientations. However, its computational complexity is very high. In this paper, we propose three tools to enhance the WBCT coding scheme, in particular, on reducing its computational complexity. First, we propose short-length 2-D filters for directional transform. Second, the directional transform is applied to only a few selected subbands and the selection is done by a mean-shift-based decision procedure. Third, we fine-tune the context tables used by the arithmetic coder in WBCT coding to improve coding efficiency and to reduce computation. Simulations show that, at comparable coded image quality, the proposed scheme saves over 92% computing time of the original WBCT scheme. Comparing to the conventional 2-D wavelet coding schemes, it produces clearly better subjective image quality. (c) 2012 Elsevier Inc. All rights reserved.

关键词： Contourlet transform Wavelet-based contourlet transform Bit-plane coding Directional filter bank Directional transform Wavelet transform Image coding computational complexity reduction Adaptive Directional Transform

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Delay-dependent stability analysis for neural networks with additive time-varying delay components

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IET CONTROL THEORY AND APPLICATIONS 2013年第3期7卷 354-362页

作者： Zhu, Xun-Lin Yue, Dong Wang, Youyi Zhengzhou Univ Dept Math Zhengzhou 450001 Peoples R China Nanjing Univ Posts & Telecommun CollAutomat Nanjing 210023 Jiangsu Peoples R China Huazhong Univ Sci & Technol Dept Control Sci & Engn Wuhan 430074 Peoples R China Nanyang Technol Univ Sch Elect & Elect Engn Singapore 639798 Singapore

This article studies the problem of stability analysis for neural networks (NNs) with two additive time-varying delay components. By taking both the independence and the variation of the two delay components into consideration, a more general Lyapunov functional is defined. By estimating the upper bound of the derivative of the Lyapunov functional more tightly, a less conservative delay-dependent stability criterion is established in terms of linear matrix inequalities. To reduce the computational complexity, a method for eliminating slack variables is provided, and then a simplified stability criterion is obtained. Some numerical examples are given to illustrate the effectiveness of the proposed method and the significant improvement over the existing results.

关键词： computational complexity delays linear matrix inequalities Lyapunov methods neural nets stability stability criteria time-varying systems delay-dependent stability analysis neural networks additive time-varying delay components general Lyapunov functional conservative delay-dependent stability criterion linear matrix inequalities computational complexity reduction slack variable elimination method computational complexity delays linear matrix inequalities Lyapunov methods neural nets stability stability criteria time-varying systems delay-dependent stability analysis neural networks additive time-varying delay components general Lyapunov functional conservative delay-dependent stability criterion linear matrix inequalities computational complexity reduction slack variable elimination method

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Dimensionality reduction to solve resource allocation problem in 5G UDN using genetic algorithm

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SOFT COMPUTING 2021年第6期25卷 4629-4642页

作者： Reyna-Orta, Adolfo Andrade, Angel G. Univ Autonoma Baja California Fac Ingn Blvd Benito Juarez S-N Col Insurgentes Mexicali 21280 Baja California Mexico

5G ultra-dense network (UDN) systems consist of massive deployment of small cells. This technology allows increasing spectral efficiency and solving the spectrum scarcity problem. However, as small cell count increases, the probability of severe interference increases, causing a network capacity degradation. The resource allocation (RA) algorithms distribute the available spectrum resources with the least interference. It is modeled as an optimization problem, and allocating the different resources results exceedingly complex. In this work, a new design approach for RA is proposed. The strategy is based on allocating a single block of channels to either users or cells instead of disjoint channels across the available spectrum. We call them user block allocation and cell block allocation, respectively. They consider a filtered search space of channel allocations providing two-dimensionality reduction levels to the channel allocation problem. The scenario evaluation consists of an unplanned UDN and a uniform small cell deployment, where at least one active user is present for each cell. The results obtained through the genetic algorithm solution on the network's spectral efficiency, cell's average capacity, and subchannel allocation rate show that the proposed arrangements alleviate the high complexity of the channel allocation problem and find feasible solutions for UDN scenarios.

关键词： Ultra-dense networks Resource allocation Genetic algorithm 5G system computational complexity reduction

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Efficient list-sphere detection scheme for joint iterative multiple-input multiple-output detection

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IET COMMUNICATIONS 2014年第18期8卷 3341-3348页

作者： Ahmed, Saleem Kim, Sooyoung Chonbuk Natl Univ Jeonju 561756 South Korea

List-sphere detection (LSD) is a sub-optimal multiple-input multiple-output (MIMO) detection scheme which searches candidate symbol vectors that lie within a sphere of a given radius. This study presents an efficient LSD based method for a joint iterative MIMO detection scheme. The proposed method utilises a channel condition in order to define the list size. During the search process, the radius is adaptively updated to reduce the computational complexity. Owing to the list size and corresponding radius are adaptively determined by the channel condition, the authors can operate the detector at the most appropriate complexity to produce the required performance. Simulation results show that the proposed methods provide substantial complexity reduction without bit error rate performance degradation.

关键词： MIMO communication iterative methods wireless channels communication complexity search problems list sphere detection scheme multiple input multiple output candidate symbol vector efflcient LSD based method joint iterative MIMO detection scheme channel condition search process computational complexity reduction

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No-reference quality measure in brain MRI images using binary operations, texture and set analysis

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IET IMAGE PROCESSING 2017年第9期11卷 672-684页

作者： Osadebey, Michael Pedersen, Marius Arnold, Douglas Wendel-Mitoraj, Katrina NeuroRx Res Inc MRI Reader Grp 3575 Parc AveSuite 5322 Montreal PQ H2X 3P9 Canada Norwegian Univ Sci & Technol Dept Comp Sci Teknologivegen 22 N-2815 Gjovik Norway McGill Univ Montreal Neurol Inst & Hosp Montreal PQ H3A 2B4 Canada BrainCare Oy Finn Medi 1 PL 2000 Tampere 33521 Finland

The authors propose a new application-specific, post-acquisition quality evaluation method for brain magnetic resonance imaging (MRI) images. The domain of a MRI slice is regarded as universal set. Four feature images;greyscale, local entropy, local contrast and local standard deviation are extracted from the slice and transformed into the binary domain. Each feature image is regarded as a set enclosed by the universal set. Four qualities attribute;lightness, contrast, sharpness and texture details are described by four different combinations of feature sets. In an ideal MRI slice, the four feature sets are identically equal. Degree of distortion in real MRI slice is quantified by fidelity between the sets that describe a quality attribute. Noise is the fifth quality attribute and is described by the slice Euler number region property. Total quality score is the weighted sum of the five quality scores. The authors' proposed method addresses current challenges in image quality evaluation. It is simple, easy-to-use and easy-to-understand. Incorporation of binary transformation in the proposed method reduces computational and operational complexity of the algorithm. They provide experimental results that demonstrate efficacy of their proposed method on good quality images and on common distortions in MRI images of the brain.

关键词： computational complexity entropy feature extraction image texture biomedical MRI brain no-reference quality measure brain MRI images binary operations set analysis application-specific post-acquisition quality evaluation method brain magnetic resonance imaging images MRI slice feature images greyscale images local entropy local contrast local standard deviation image texture lightness image contrast image sharpness texture details quality attribute Euler number region quality score image quality evaluation operational complexity reduction computational complexity reduction MRI image distortions

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Motion estimation with low resolution distortion metric

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ELECTRONICS LETTERS 2005年第12期41卷 693-694页

作者： Agha, S Dwyer, VM Chouliaras, V Univ Loughborough Dept Elect & Elect Engn Loughborough LE11 3LP Leics England

Considering all possible candidate motion vectors in a given search area and calculating a distortion measure at every search position, as with the full-search block-matching motion estimation algorithm (FSBME), places a prohibitively high computational burden on the video encoder, making it unsuitable for real-time/portable video applications. To reduce computational complexity while maintaining accuracy, a new version of the reduced-bit, sum of absolute difference (RBSAD) algorithm is presented, which allows for optional correction to full resolution (FSBME) when appropriate. Analysis of a number of video sequence shows that this correction is required for blocks for which there is little motion between frames.

关键词： image matching image resolution image sequences motion estimation videocoding computational complexity reduction full search block matching motion estimation algorithm low resolution distortion metric reduced-bit sum of absolute difference algorithm sea

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Synthetic transmit aperture focusing using optimal sparse receive array for reducing computational complexity

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ELECTRONICS LETTERS 2016年第4期52卷 253-254页

作者： Park, J. Song, T. -K. Sogang Univ Sch Engn Dept Elect Engn 1 Sinsu Dong Seoul South Korea

Synthetic transmit aperture focusing (STAF) has the problem of high computational complexity. An STAF scheme with greatly reduced computational complexity by using an optimal periodic sparse receive array (SRA) is proposed. An analytic method to design optimal SRAs that provide minimum main lobe width and grating lobe levels for a given number of active receive elements is also suggested. The experiment results show that the proposed STAF method can reduce computational complexity by up to 66.67% compared with conventional STAF.

关键词： computational complexity array signal processing grating lobe levels minimum main lobe width optimal SRA design SRA optimal periodic sparse receive array STAF scheme computational complexity reduction synthetic transmit aperture focusing scheme

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