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International Siberian conference on Control and Communications

作者： Daniil A. Loktev Alexey A. Loktev Department of Information Systems and Telecommunications Bauman Moscow State Technical University Moscow Russia Department of Transport Construction Moscow State University of Railway Engineering Moscow Russia

ISBN: (纸本)9781467383844

An important element of the modern automated control systems, monitoring and remote access is to obtain primary information about the state and behavior of static or moving objects. To obtain such information we propose to use photo and video detectors, which could provide images of objects with high resolution in the system. Thus, the possibility of determining the geometric and kinematic parameters of the moving object are significantly reduced because of the different aspects of producing an image, one of these aspects is the blur. The geometric parameters of the object are determined by analyzing the blur of its images obtained at different settings of the photodetector. In this paper, algorithms of processing of primary information are improved by the use of methods and procedures of statistical analysis and probabilistic approach. It increases the accuracy of determined characteristics, the applicability of procedures for the calculation of state parameters (size, shape, distance from observer) and behavior parameters of the object (speed and direction) and reduces the computational complexity of the final algorithm. The research allows not only determine the geometric parameters of the object, but also to evaluate their accuracy and to develop elements of the algorithm that can be used in real systems of video monitoring

关键词： image blur video monitoring system method of least squares method of least modules object geometric parameters Bayesian estimation loss function distribution function of errors

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Direct fisheye stereo correspondence using enhanced unified camera model and semi-global matching algorithm

Direct fisheye stereo correspondence using enhanced unified ...

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International conference on Control, Automation, Robotics and Vision

作者： Bogdan Khomutenko Gaetan Garcia Philippe Martinet IRCCYN Ecole Centrale de Nantes (ECN) Nantes France

ISBN: (纸本)9781509035502

In this paper, it is shown that the Enhanced Unified Camera Model, which is used to model fisheye cameras, projects straight lines into conic sections. Then a way to find equations of straight line projections is proposed. The method is applied to epipolar curves to adapt the Semi-Global Matching algorithm to fisheye stereo systems to compute a dense direct stereo correspondence without undistortion and rectification of fisheye images. It is done by efficient image sampling along an epipolar curve, using an algorithm for rasterization of implicit curves. A C++ implementation is available online.

关键词： Camera Model Raster processing image samples rectification distilling Implicit Acoustic equipment Correspondence Curves algorithms Conic

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An l1-regularized least squares algorithm for reconstructing step-frequency ground penetrating radar images

An l1-regularized least squares algorithm for reconstructing...

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IEEE National conference on Radar

作者： Henry C. Ogworonjo John M. M. Anderson Mandoye Ndoye Lam Nguyen Department of Electrical and Computer Engineering Howard University Washington DC Department of Electrical Engineering Tuskegee University Tuskegee AL U. S Army Research Laboratory Adelphi Maryland

ISBN: (纸本)9781509008643

Impulse-based ground penetrating radar (GPR) has been proposed as a way to detect landmines and improvised explosive devices (IEDs). However, a drawback of such radar systems is the difficulty in transmitting a signal with an arbitrary bandwidth and shape. Step-frequency GPR has been recognized as a way to precisely control the bandwidth and spectral shape of the transmitted pulse. In this paper, we extend a previously developed ℓ 1 -regularized least squares algorithm, which has been successfully applied to impulse-based GPR image reconstruction, to step-frequency GPR. We investigate the performance of the proposed algorithm using simulated step-frequency GPR data. The initial results are promising.

关键词： Ground penetrating radar Signal processing algorithms image reconstruction Linear programming Receiving antennas Radar imaging

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Real-time multi-resolution digital elevation map creation using the sensor model of a stereovision sensor

Real-time multi-resolution digital elevation map creation us...

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International conference on Intelligent Transportation

作者： Szilárd Mandici Sergiu Nedevschi Image Processing and Pattern Recognition Research Group Technical University of Cluj-Napoca Romania

ISBN: (纸本)9781509018901

This paper presents an approach for constructing high quality Digital Elevation Maps (DEMs) from dense stereo data. As opposed to classical DEM creation algorithms, the proposed solution uses the sensor models of the stereovision sensor to correct the raw data. The direct and inverse sensor models are found from experiments. The algorithm decomposes the 2D cells containing vertical objects or object boundaries in order to model the objects more precisely. The approach distinguishes between 2 types of cells: cells containing horizontal and vertical objects. For the vertical object cells, connected components in the histogram of heights are found while in the horizontal object cells, the most representative height is determined using a mode-seeking approach similar to mean shift. The 3D reconstructed points are assigned to the cells around it by considering the probability of correspondence based on the 2D Gaussian component of the direct sensor model. In order to eliminate the noise, a similarity measure is computed between each 3D point and cell based on the calculated DEM cell descriptor and is discarded if the similarity score is smaller than a predefined threshold. The algorithm is implemented on the GPU in order to achieve a real-time execution speed and it is evaluated extensively in comparison with other DEM creation algorithms using the latest KITTI stereo benchmark data. The obtained DEM is denser, more accurate and the object boundaries are modeled more precisely.

关键词： Three-dimensional displays Robot sensing systems image reconstruction Two dimensional displays Histograms Solid modeling Mathematical model

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Piecewise-polynomial curve fitting using group sparsity

Piecewise-polynomial curve fitting using group sparsity

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International conference on Ultra Modern Telecommunications and Workshops (ICUMT)

作者： Michaela Novosadová Pavel Rajmic Dept. of Telecommunications Brno University of Technology Brno Czech Republic

ISBN: (纸本)9781467388191

We present a method for segmenting one-dimensional signal, whose segments are modeled as polynomials, and which is corrupted by an additive noise. The method is based on sparse modeling and its formulation as a convex optimization problem is solved by proximal algorithms. We perform experiments on simulated data, discuss the results and suggest future directions that could lead to even better results.

关键词： Convergence image segmentation TV Convex functions Telecommunications Signal processing Iterative methods

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Multilevel Thresholding image Segmentation Using Memetic Algorithm 6

Multilevel Thresholding Image Segmentation Using Memetic Alg...

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6th International conference on Information and Communication systems (ICICS)

作者： Banimelhem, Omar Mowafi, Moad Alzoubi, Oduy Jordan Univ Sci & Technol Dept Network Engn & Secur Irbid Jordan Jordan Univ Sci & Technol Dept Comp Engn Irbid Jordan

ISBN: (纸本)9781479973491

Memetic algorithms (MAs) are hybrid algorithms aimed to improve traditional evolutionary algorithms such as genetic algorithms (GAs). Recently, MAs have been widely used in the image processing field. This paper proposes an image segmentation approach using MA. The proposed approach employs local search as an improvement operator added to the GA in order to speed up the searching process and generate the best solutions faster. The results of the experiments that were conducted on eight different images have shown that MA converges to the solutions faster than GA. In terms of processing time, MA has recorded significant improvement ranging from 17.5% to 79.8%. The comparison results have also shown that MA always achieves the same or better quality of the segmented images.

关键词： image segmentation multilevel thresholding genetic algorithm memetic algorithm

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Variational mode feature-based hyperspectral image classification

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Advances in Intelligent systems and Computing 2016年 380卷 365-373页

作者： Nechikkat, Nikitha Sowmya, V. Soman, K.P. Center for Excellence in Computational Engineering and Networking Amrita Vishwa Vidyapeetham CoimbatoreTamil Nadu India

ISBN: (纸本)9788132225225

Hyperspectral image analysis is considered as a promising technology in the field of remote sensing over the past decade. There are various processing and analysis techniques developed that interpret and extract the maximum information from high-dimensional hyperspectral datasets. The processing techniques significantly improve the performance of standard algorithms. This paper uses variational mode decomposition (VMD) as the processing algorithm for hyperspectral data scenarios followed by classification based on sparse representation. Variational Mode Decomposition decomposes the experimental data set into few different modes of separate spectral bands, which are unknown. These modes are given as raw input to the classifier for performance analysis. Orthogonal matching pursuit (OMP), the sparsity-based algorithm is used for classification. The proposed work is experimented on the standard dataset, namely Indian pines collected by the airborne visible/infrared imaging spectrometer (AVIRIS). The classification accuracy obtained on the hyperspectral data before and after applying Variational Mode Decomposition was analyzed. The experimental result shows that the proposed work leads to an improvement in the overall accuracy from 84.82 to 89.78%, average accuracy from 85.03 to 89.53% while using 40% data pixels for training. © Springer India 2016.

关键词： Variational mode decomposition

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Super Resolution Algorithm for CCTVs 13

Super Resolution Algorithm for CCTVs

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conference on image processing - algorithms and systems XIII

作者： Gohshi, Seiichi Kogakuin Univ Shinjuku Ku Tokyo 1638677 Japan

ISBN: (纸本)9781628414899

Recently, security cameras and CCTV systems have become an important part of our daily lives. The rising demand for such systems has created business opportunities in this field, especially in big cities. Analogue CCTV systems are being replaced by digital systems, and HDTV CCTV has become quite common. HDTV CCTV can achieve images with high contrast and decent quality if they are clicked in daylight. However, the quality of an image clicked at night does not always have sufficient contrast and resolution because of poor lighting conditions. CCTV systems depend on infrared light at night to compensate for insufficient lighting conditions, thereby producing monochrome images and videos. However, these images and videos do not have high contrast and are blurred. We propose a nonlinear signal processing technique that significantly improves visual and image qualities (contrast and resolution) of low-contrast infrared images. The proposed method enables the use of infrared cameras for various purposes such as night shot and poor lighting environments under poor lighting conditions.

关键词： CCTV Real-time Video processing Nyquist Frequency Super Resolution Super Resolution image Reconstmction 8K TV

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Marine Vessel Detection Comparing GPRS and Satellite images for Security Applications

Marine Vessel Detection Comparing GPRS and Satellite Images ...

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International conference on Wireless Communications, Signal processing and Networking

作者： Sajan Amabdiyil V. P. Mahadevan Pillai Dintu Thomas Optical Image processing & Security products Centre for Development of Imaging Technology Thiruvanthapuram-695027 Kerala India Communication Engineering Department SCMS School of Engineering and Technology Ernakulum Kerala India Department of Optoelectronics University of Kerala Kariavattom Thiruvanthapuram-69558 India

ISBN: (纸本)9781467393393

Unauthorized and unregistered sea going fishing vessels are being used for criminal activities in the coastal areas. The issue of piracy against merchant ships using illegal fishing vessels poses a significant threat to world shipping. Unfortunately counter piracy efforts and maritime security of our own and other nation enforcement often affects the innocent fishermen who conduct the trans-border fishing. Hence a proper vessel monitoring system is required to protect the maritime security without tampering the routine fishing activity of the sea going fishermen. This paper discusses about the feasibility of a system for the detection of registered marine fishing vessels comparing the satellite images and GPRS signal information. A review on various algorithms for identifying marine boats from satellite images is also conducted in this paper.

关键词： Vessel Monitoring systems Satellite images GPRS Trans-border fishing

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Model-based Detection, Segmentation, and Classification of Compact Objects 24

Model-based Detection, Segmentation, and Classification of C...

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conference on Signal processing, Sensor/Information Fusion, and Target Recognition XXIV

作者： Carlotto, Mark J. Gen Dynam Adv Informat Syst Pittsfield MA 01201 USA

ISBN: (纸本)9781628415902

A unified model-based approach to ATR that uses 3D models to control detection, segmentation, and classification is described. Objects are modeled by rectangular boxes whose dimensions are Gaussian random variables. A fast predictor estimates the size and shape of expected objects in the image, which controls detection and segmentation algorithms. Segmentation fits oriented rectangles (length x width @ pose) to object-like regions detected using a multi-level thresholding/region tracking approach. Detections are classified by comparing measured to predicted region length and width in the pose direction. The method is fast and requires only a coarse characterization of objects/object classes.

关键词： image segmentation 3D modeling Optical tracking systems modeling Binary data Sensors Automatic target recognition Classification systems Detection and tracking algorithms image processing algorithms and systems

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