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Localization algorithms for multilateration (MLAT) systems in airport surface surveillance

SIGNAL image AND vIDEO processing 2015年第7期9卷 1549-1558页

作者： Mantilla-Gaviria, Ivan A. Leonardi, Mauro Galati, Gaspare Balbastre-Tejedor, Juan v. Univ Politecn Valencia Inst ITACA Valencia 46022 Spain Univ Roma Tor Vergata DIE I-00133 Rome Italy

We present a general scheme for analyzing the performance of a generic localization algorithm for multilateration (MLAT) systems (or for other distributed sensor, passive localization technology). MLAT systems are used for airport surface surveillance and are based on time difference of arrival measurements of Mode S signals (replies and 1,090 MHz extended squitter, or 1090ES). In the paper, we propose to consider a localization algorithm as composed of two components: a data model and a numerical method, both being properly defined and described. In this way, the performance of the localization algorithm can be related to the proper combination of statistical and numerical performances. We present and review a set of data models and numerical methods that can describe most localization algorithms. We also select a set of existing localization algorithms that can be considered as the most relevant, and we describe them under the proposed classification. We show that the performance of any localization algorithm has two components, i.e., a statistical one and a numerical one. The statistical performance is related to providing unbiased and minimum variance solutions, while the numerical one is related to ensuring the convergence of the solution. Furthermore, we show that a robust localization (i.e., statistically and numerically efficient) strategy, for airport surface surveillance, has to be composed of two specific kind of algorithms. Finally, an accuracy analysis, by using real data, is performed for the analyzed algorithms;some general guidelines are drawn and conclusions are provided.

关键词： Localization algorithms Multilateration Time difference of arrival Airport surface surveillance Air traffic control

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An image processing vLIW Architecture for Real-Time Depth Detection

An Image Processing VLIW Architecture for Real-Time Depth De...

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International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD)

作者： Dan Iorga Razvan Nane Yi Lu Edwin van Dalen Koen Bertels Computer Engineering Research Group Delft University of Technology Delft The Netherlands Intel Benelux B.V Eindhoven AG The Netherlands Intel Benelux B.V. Eindhoven Netherlands

ISBN: (纸本)9781509061099

Numerous applications for mobile devices require 3D vision capabilities, which in turn require depth detection since this enables the evaluation of an object's distance, position and shape. Despite the increasing popularity of depth detection algorithms, available solutions need expensive hardware and/or additional ASICs, which are not suitable for low-cost commodity hardware devices. In this paper, we propose a low-cost and low-power embedded solution to provide high speed depth detection. We extend an existing off-the-shelf vLIW image processor and perform algorithmic and architectural optimizations in order to achieve the requested real-time performance speed. Experimental results show that by adding different functional units and adjusting the algorithm to take full advantage of them, a 640×480 image pair with 64 disparities 1 can be processed at 36.75 fps on a single processor instance, which is an improvement of 23% compared to the best state-of-the-art image processor.

关键词： vLIW Hardware Computer architecture Real-time systems Optimization Kernel Performance evaluation

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A survey on texture synthesis and its approaches

A survey on texture synthesis and its approaches

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International Conference on Computing Technologies and Intelligent Data Engineering (ICCTIDE)

作者： S. Ramya N.v. Shibu P. Malathi Computer Science and Engineering Sri Ramakrishna Institute of Technology Coimbatore India Bharathiyar Institute of Engineering For Womens Salem India

ISBN: (纸本)9781467384384

Texture synthesis is a fast growing technique in image processing, and has been widely used in real time processes. During this process a texture is taken as sample input and various methods and techniques are applied to synthesis that texture to produce a large synthesized texture with user defined size and similar texture characteristics. Methods and techniques used are tiling and synthesis based on patches, pixels and exemplar. Quality of the synthesized texture and synthesis time is one of the major concerns during the process. A survey is taken on various techniques used to improve the quality and synthesis time of the texture.

关键词： Real-time systems Algorithm design and analysis Support vector machines image color analysis Genetic algorithms Computer science Mobile communication

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Supervised Evaluation of Seed-Based Interactive image Segmentation algorithms 20

Supervised Evaluation of Seed-Based Interactive Image Segmen...

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20th SYMPOSIUM ON SIGNAL processing, imageS AND COMPUTER vISION (STSIvA)

作者： Andrade, Fernanda Carrera, Enrique v. Univ Fuerzas Armadas ESPE Casilla 171-5-231B Sangolqui Ecuador

ISBN: (纸本)9781467394611

Extensive research has been conducted in an effort to evaluate methods and techniques for image segmentation. However, while most literature has focused on evaluating automatic and semi-automatic algorithms, works evaluating interactive segmentation algorithms are less numerous. Note that interactive segmentation can improve results by adding prior knowledge from users into the process. Although this user guidance improves segmentation results, it also makes difficult to conduct objective evaluations. For this reason, some works only present non-canonical evaluations. In this paper, we present an objective and empirical evaluation of seed-based interactive segmentation algorithms. We first compare popular metrics that are employed in image-segmentation evaluations in order to define which one reflects most accurately the performance of segmentation algorithms. Then, in the aim of presenting reproducible results, we introduce a novel seed-based user input dataset that extends the well-known GrabCut dataset. In addition, we evaluate and contrast four state-of-the-art interactive segmentation algorithms. The analysis of the results demonstrates that Jaccard coefficient and Precision-Recall curves provide a good insight into the performance of the evaluated algorithms. Finally, the GrabCut algorithm presents the most robust and useful segmentation among all the evaluated algorithms.

关键词： image segmentation interactive systems GrabCut algorithm GrabCut dataset Jaccard coefficient objective evaluations precision-recall curves seed-based interactive image segmentation algorithms seed-based user input dataset segmentation results semiautomatic algorithms supervised evaluation Accuracy Algorithm design and analysis Databases image color analysis image segmentation Measurement Semantics image segmentation Algorithm design and analysis image colour analysis interactive systems image segmentation algorithm Semantics segmentation Database Segmentation Interactive

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Fast Change Detection for Camera-based Surveillance systems

Fast Change Detection for Camera-based Surveillance Systems

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IEEE International Conference on Intelligent Transportation systems

作者： Matthias Michael Christian Feist Florian Schuller Marc Tschentscher University of Bochum Institute for Neural Computation AUDI AG

ISBN: (纸本)9781509018901

Many parking garages and open parking spaces today are already equipped with surveillance cameras to increase the security of pedestrians or to record potentially illegal actions. An additional use case for such multi-camera surveillance systems is the automatic extraction of 3D-positions of objects and pedestrians. The safety of autonomous vehicles could benefit from this information in cases where the on-board sensors might be unable to detect potentially dangerous situations due to occlusion. Since the used cameras are installed statically, change detection is often employed as the first operation and all subsequent processing steps rely on its quality. Different scenarios impose specific challenges to the respective algorithms. In this paper we present an efficient algorithm for change detection which is tailored to the difficulties arising in an indoor surveillance scenario and demonstrate its applicability by adapting an existing pipeline and improving overall performance.

关键词： SURvEILLANCE systems Pedestrians Fasting Detective cameras automatic extracting Autonomous vehicles efficient algorithm Parking garages Cameras PARKING SPACE image change detection Occlusion

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Early detection and categorization of cataract using slit-lamp images by hough circular transform

Early detection and categorization of cataract using slit-la...

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International Conference on Communications and Signal processing

作者： Amol B. Jagadale D. v. Jadhav Pursuing his PhD in Electronics at (RSCOE) Rajarshi Shahu College of Engineering Savitribai Phule Pune University Tathawade Pune INDIA Working as PhD guide for (RSCOE) Rajarshi Shahu College of Engineering Savitribai Phule Pune University Tathawade Pune INDIA

ISBN: (纸本)9781467385497

CATARACT is a loss of the normal transparency of human lens due to opacity. The lens is mostly made of water and protein. A cataract is formed when the protein clumps together, which clouds the lens and reduces the light that reaches the retina. Age-related cataract is the leading cause of visual loss globally. The age-related cataract can be classified into three types according to the location of opacity in the lens as nuclear cataract, cortical cataract and post sub-capsular cataract. Nuclear cataract is the most common of all cataract types. It starts off at the center of the lens and progresses towards the surface. The slit-lamp photography is the main means of nuclear cataract imaging. It is based on reflected light. The camera and slit are placed obliquely to the visual axis of the eye to capture an image of the cross-section of the eye. The ability to best capture anterior sections of the eye makes it an ideal approach for grading nuclear cataracts. Clinically, ophthalmologists evaluated the degree of cataract by comparing the picture observed through camera with a series of standard photographs, which is termed as clinical grading such as Lens Opacities Classification System III (LOCSIII). The manual grading system causes intra-grader and inter-grader variations. With the development of image processing techniques, efforts have been put in the development of automatic systems to improve grading objectivity. For nuclear cataract classification, automatic systems were proposed using slit-lamp images.

关键词： Iris Transforms Lenses Detection algorithms Gray-scale Feature extraction Cameras

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No-reference visual quality assessment for image inpainting 13

No-reference visual quality assessment for image inpainting

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Conference on image processing - algorithms and systems XIII

作者： voronin, v. v. Frantc, v. A. Marchuk, v. I. Sherstobitov, A. I. Egiazarian, K. Don State Tech Univ Dept Radioelect Syst Shakhty 346500 Russia Tampere Univ Technol Dept Signal Proc FI-33720 Tampere Finland

ISBN: (纸本)9781628414899

Inpainting has received a lot of attention in recent years and quality assessment is an important task to evaluate different image reconstruction approaches. In many cases inpainting methods introduce a blur in sharp transitions in image and image contours in the recovery of large areas with missing pixels and often fail to recover curvy boundary edges. Quantitative metrics of inpainting results currently do not exist and researchers use human comparisons to evaluate their methodologies and techniques. Most objective quality assessment methods rely on a reference image, which is often not available in inpainting applications. Usually researchers use subjective quality assessment by human observers. It is difficult and time consuming procedure. This paper focuses on a machine learning approach for no-reference visual quality assessment for image inpainting based on the human visual property. Our method is based on observation that Local Binary Patterns well describe local structural information of the image. We use a support vector regression learned on assessed by human images to predict perceived quality of inpainted images. We demonstrate how our predicted quality value correlates with qualitative opinion in a human observer study. Results are shown on a human-scored dataset for different inpainting methods.

关键词： inpainting quality assessment metric SvR visual salience machine learning

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Generation of synthetic infrared images and their visual quality estimation using deep convolutional neural networks

Scientific Visualization

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Scientific visualization 2016年第4期8卷 67-79页

作者： Kniaz, vladimir v. Gorbatsevich, vladimir S. Mizginov, vladimir A. Federal State Unitary Enterprise 'State Research Institute of Aviation Systems' GosNIIAS Moscow Russia

In recent years deep convolutional neural networks became a powerful tool for object recognition. Accuracy of deep convolutional neural networks is comparable with the accuracy of a human operator. Convolutional networks also provide a flexible framework for hyperspectral image processing. The simultaneous usage of images that were captured using sensors of different wavelengths increases the probability of the correct classification. To achieve a high accuracy of classification during the learning process it is required to have a large number of images in the training dataset. Training images should be captured under various conditions. A number of large image datasets (Pascal vOC, MS COCO) for training of image classification algorithms are available in the open access nowadays. However, training of image classification algorithm for classification of infrared images is more complex as large datasets of infrared images are not available in the open access. This paper is focused on the development of a method for augmentation of images captured in the visible wavelength with synthetic infrared images. The method is based on the rendering of textured 3D-models of objects of interest and generation of pseudo-infrared background textures from a source image captured in the visible wavelength. An algorithm for registration of real images and 3D-models is presented. A dedicated algorithm for object tracking in complex environment is discussed. The proposed method was used to generate a large learning dataset for detection of foreign objects on a runway. To evaluate the quality of synthetic images a special quality measure is proposed. The measure is based on the accuracy of a deep neural network. The paper is concluded with the discussion of the accuracy of deep convolutional neural network classifier trained on the dataset that were generated using the proposed method.

关键词： Object recognition

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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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Estimation of Measurement of Distance to the Object by Analyzing the Blur of Its image Series

Estimation of Measurement of Distance to the Object by Analy...

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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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