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检索条件"任意字段=Conference on Image Processing - Algorithms and Systems VII"

共 12978 条记录，以下是4941-4950 订阅

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A hybrid algorithm for dense stereo correspondences in challenging indoor scenes

A hybrid algorithm for dense stereo correspondences in chall...

引用

IEEE International Workshop on Imaging systems and Techniques (IST)

作者： Stavros Georgousis Christos Stentoumis Nikolaos Doulamis Athanasios Voulodimos National Technical University of Athens Athens Greece

ISBN: (纸本)9781509018185

The algorithms for dense correspondences in stereo images are an extensively researched topic, since it is an essential step in a large number of applications. Despite the fact that the first stereo matching algorithms were proposed some decades ago, novel approaches regarding typical, but also cutting-edge applications, are always in demand. Stereo matching is an inverse, ill-posed problem, which usually depends on the application and the scenario. In this contribution, a hybrid approach for stereo matching is proposed, which is based on graph-cuts optimization (global) and cross-based aggregation (local) under a hierarchical scheme. It is shown that the combined effect of a global method in a coarse layer and a local method in finer layers improves the matching results. This hybrid approach exploits the strengths and ameliorates the weaknesses of the individual global and local algorithms. The resulted disparity map is robust without outliers even in untextured areas and at the same time high fidelity details are accurately represented. This hybrid scheme is evaluated on challenging indoor datasets. It is also computationally efficient for applying it on low-processing power applications.

关键词： Transforms Cost function image resolution Robustness Three-dimensional displays Cameras

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Design and manufacturing of a low-cost 2-DOF autonomous sentry gun

Design and manufacturing of a low-cost 2-DOF autonomous sent...

引用

International conference on Robotics and Artificial Intelligence (ICRAI)

作者： Husnain Ahmad Syed Mohsin Ali Usman Ayub Sheikh Zain Murtaza Muhammad Rizwan Department of Robotics and Artificial Intelligence National University of Sciences and Technology Islamabad Pakistan Electrical and Automation Department Automation Test and Control Institute Harbin Institute of Technology Harbin China

ISBN: (纸本)9781509040605

In this paper, design and development of a self-sufficient sentry robotic gun is presented. Professional robotic assemblies which are generally developed for security purposes are targeted toward high efficiency and are based on extensive control algorithms. This makes them quite expensive and infeasible for low budget applications. One important component of such systems is that of motion detection. Motion detection also plays a key role in security applications installed at banks, offices and vulnerable areas. An efficient motion detection system has been developed using embedded micro-controller and MATLAB interface. The proposed system can also be set into an autonomous mode of operation, in which the system tracks and engages targets without any human intervention. Aside from autonomous mode, there is also a manual over-ride mode. The hardware employed in the proposed system is based on easily accessible materials. Motion detection and image processing was implemented using MATLAB image processing toolbox and periodic background estimation subtraction was used for the detection of motion.

关键词： Weapons Servomotors Motion detection MATLAB Registers Torque image processing

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WATERSHED SUPERPIXEL

WATERSHED SUPERPIXEL

引用

IEEE International conference on image processing (ICIP)

作者： Hu, Zhongwen Zou, Qin Li, Qingquan Shenzhen Univ Shenzhen Key Lab Spatial Smart Sensing & Serv Shenzhen Peoples R China Wuhan Univ Sch Comp Sci Wuhan Peoples R China

ISBN: (纸本)9781479983391

As a pre-processing tool, superpixel algorithms have been popular used in many computer -vision applications. High efficiency is a desired property of superpixel algorithms, especially in real-time vision systems. In this paper, a novel high -efficient superpixel algorithm is developed based on the watershed algorithm, namely the spatial -constrained watershed (SCoW). SCoW performs watersheding in a marker controlled manner, with a set of evenly placed markers. To align superpixel boundaries to image edges, an edge preserving scheme is embedded into the SCoW which makes a balance between the homogeneity and the compactness. Without any complex computing, the proposed superpixel algorithm is found to produce high quality superpixels as traditional superpixel algorithms, while holding much higher efficiency.

关键词： superpixel watershed spatial constraint image segmentation

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Threat image Projection (TIP) into X-ray images of cargo containers for training humans and machines

Threat Image Projection (TIP) into X-ray images of cargo con...

引用

International Carnahan conference on Security Technology

作者： Thomas W. Rogers Nicolas Jaccard Emmanouil D Protonotarios James Ollier Edward J. Morton Lewis D. Griffin Dept. Security & Crime Sciences University College London Dept. Computer Science University College London Rapiscan Systems Ltd. Stoke-on-Trent UK

ISBN: (纸本)9781509010738

We propose a framework for Threat image Projection (TIP) in cargo transmission X-ray imagery. The method exploits the approximately multiplicative nature of X-ray imagery to extract a library of threat items. These items can then be projected into real cargo. We show using experimental data that there is no significant qualitative or quantitative difference between real threat images and TIP images. We also describe methods for adding realistic variation to TIP images in order to robustify Machine Learning (ML) based algorithms trained on TIP. These variations are derived from cargo X-ray image formation, and include: (i) translations; (ii) magnification; (iii) rotations; (iv) noise; (v) illumination; (vi) volume and density; and (vii) obscuration. These methods are particularly relevant for representation learning, since it allows the system to learn features that are invariant to these variations. The framework also allows efficient addition of new or emerging threats to a detection system, which is important if time is critical. We have applied the framework to training ML-based cargo algorithms for (i) detection of loads (empty verification), (ii) detection of concealed cars (ii) detection of Small Metallic Threats (SMTs). TIP also enables algorithm testing under controlled conditions, allowing one to gain a deeper understanding of performance. Whilst we have focused on robustifying ML-based threat detectors, our TIP method can also be used to train and robustify human threat detectors as is done in cabin baggage screening.

关键词： X-ray imaging Containers Training Lighting Detectors Visualization Robustness

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An Adherent Raindrop Detection Method Using MSER

An Adherent Raindrop Detection Method Using MSER

引用

Asia-Pacific-Signal-and-Information-processing-Association Annual Summit and conference (APSIPA ASC)

作者： Ito, Koichi Noro, Kazumasa Aoki, Takafumi Tohoku Univ Grad Sch Informat Sci Aoba Ku 6-6-05 Aramaki Aza Sendai Miyagi 9808579 Japan

ISBN: (纸本)9789881476807

image processing algorithms used in surveillance systems are designed to work under good weather conditions. For example, in a rainy day, raindrops are adhered to camera lenses and windshields, resulting in partial occlusions in acquired images, and making performance of image processing algorithms significantly degraded. To improve performance of surveillance systems in a rainy day, raindrops have to be automatically detected and removed from images. Addressing this problem, this paper proposes an adherent raindrop detection method from a single image which does not need training data and special devices. The proposed method employs image segmentation using Maximally Stable Extremal Regions (MSER) and qualitative metrics to detect adherent raindrops from the result of MSER-based image segmentation. Through a set of experiments, we demonstrate that the proposed method exhibits efficient performance of adherent raindrop detection compared with conventional methods.

关键词： image segmentation

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Low Power Signal processing via Approximate Multiplier for Error-Resilient Applications

Low Power Signal Processing via Approximate Multiplier for E...

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IEEE International conference on Industrial and Information systems

作者： Bharat Garg G K Sharma ABV-Indian Institute of Information Technology and Management Gwalior India

The exponentially enlarging usability and mushrooming features in the portable hand-held devices such as cellphone appeal for the highly energy-efficient designs as the user cannot tolerate power famished devices rather can manage with tiny degraded quality. The multimedia applications such as image/video processing are compute-intensive and require efficient designs which can be achieved by approximate designs with the feeble accord in accuracy. As multiplication is the most frequently used and highly energy-consuming arithmetic operation, in this paper, a low power approximate multiplier architecture (AMA) is proposed that significantly improves the design metrics. We evaluate the proposed AMA with various quality metrics and design an AMA embedded Gaussian smoothing filter (GSF). The simulation results show that AMA reduces 81.5% power consumption over accurate and 19.17% energy over the well-known approximate multiplier architecture. Further, the AMA embedded GSF reduces 6.2% area and 7.53% power consumption over the best known approximate multiplier embedded GSF.

关键词： Adders Computer architecture Approximation algorithms Algorithm design and analysis Smoothing methods Delays Algorithm design and analysis smoothing methods adders Computer Architecture Approximation algorithms Multiplying circuits Approximate energy-efficient design delay hand-held equipment arithmetic operation

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Vehicle Black Box with 24GHz FMCW Radar

Vehicle Black Box with 24GHz FMCW Radar

引用

IEEE Region 10 conference

作者： Jung-Hwan Kim Sun-Kyu Kim Sang-Hyuk Lee Tae-Min Lee Joonhong Lim Department of Electronic Systems Engineering Hanyang University Seoul Republic of Korea

ISBN: (纸本)9781509025985

This paper presents vehicle black box using camera image and 24GHz Frequency Modulation Continuous Wave (FMCW) radar. Currently, almost all of vehicle black boxes are recording driving data using a single camera. They have some problems on low image quality and narrow viewing angle. In addition, it is difficult to record a clean image when the weather is in bad condition due to heavy rain, snow and night. These problems may have some troubles to investigate car accident accurately. In this paper, we propose a novel black box fusing data from radar and cameras. We estimate the distance and velocity of obstacle using the Doppler Effect and FMCW radar. In particular, we compare various Direction of Arrival (DOA) algorithms for estimation of obstacle angle. The experimental results indicate that the Multiple Signal Classification (MUSIC) is more accurate compared to other methods. Moreover, we formulate the vehicle tracking image through the camera image processing and radar information. This image can be used to widen viewing angle and it may be helpful to investigate a car accident. The experimental study results indicate that the new black box overcome the disadvantages of the current black boxes and may be useful for safe driving and accurate accident investigation.

关键词： FMCW Radar Vehicle Black Box Camera image processing Beamforming DOA MUSIC Root-MUSIC

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High-fidelity simulation for evaluating robotic vision performance

High-fidelity simulation for evaluating robotic vision perfo...

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IEEE/RSJ International conference on Intelligent Robots and systems

作者： John Skinner Sourav Garg Niko Sunderhauf Peter Corke Ben Upcroft Michael Milford ARC Centre of Excellence for Robotic Vision Queensland University of Technology (QUT) Brisbane Australia

ISBN: (纸本)9781509037636

Robotic vision, unlike computer vision, typically involves processing a stream of images from a camera with time varying pose operating in an environment with time varying lighting conditions and moving objects. Repeating robotic vision experiments under identical conditions is often impossible, making it difficult to compare different algorithms. For machine learning applications a critical bottleneck is the limited amount of real world image data that can be captured and labelled for both training and testing purposes. In this paper we investigate the use of a photo-realistic simulation tool to address these challenges, in three specific domains: robust place recognition, visual SLAM and object recognition. For the first two problems we generate images from a complex 3D environment with systematically varying camera paths, camera viewpoints and lighting conditions. For the first time we are able to systematically characterise the performance of these algorithms as paths and lighting conditions change. In particular, we are able to systematically generate varying camera viewpoint datasets that would be difficult or impossible to generate in the real world. We also compare algorithm results for a camera in a real environment and a simulated camera in a simulation model of that real environment. Finally, for the object recognition domain, we generate labelled image data and characterise the viewpoint dependency of a current convolution neural network in performing object recognition. Together these results provide a multi-domain demonstration of the beneficial properties of using simulation to characterise and analyse a wide range of robotic vision algorithms.

关键词： robot vision Cameras images high fidelity object recognition image data Simulation models Environments simulating Lighting

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Night-time vehicle detection using low exposure video enhancement and lamp detection

Night-time vehicle detection using low exposure video enhanc...

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International conference on Electronics, Information and Communications (ICEIC)

作者： Jin-Woo Park Byung Cheol Song Department of Electronic Engineering Inha University Incheon Republic of Korea

ISBN: (纸本)9781467380171

This paper proposes a vehicle detection algorithm using pre-processing and lamp detection at night-time. First, we present a vehicle detection using contrast enhancement. By applying a specific contrast enhancement to night-time images with low exposure, we can enhance salient features even at dark night-time. Next, we detect a pair of rear lamps from the pre-processed image(s). Finally, we can find forward vehicle(s) by lamp pairing. Experimental results show that the proposed algorithm provides reliable detection accuracy.

关键词： Vehicle detection Vehicles Classification algorithms image color analysis Training Advanced driver assistance systems Computer vision

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Comparative performance study of word segmentation techniques for handwritten odia documents

Comparative performance study of word segmentation technique...

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International conference on Signal processing, Communication, Power and Embedded System (SCOPES)

作者： Ayush Pradhan Sidharth Behera Ganapati Panda Babita Majhi Computer Science Engineering National Institute of Technology Rourkela School of Electrical and Computer Engineering Indian Institute of Technology Bhubaneswar Department of Computer Science and IT Central University Bilaspur India

ISBN: (纸本)9781509046218

Word segmentation of handwritten documents is a vital step in the Optical Character Recognition system as its accuracy greatly influences the overall recognition performance. In the literature, various methods have been proposed for word segmentation of handwritten documents of various languages. However, it is observed that for Odia, which is an important Indian language, very little work has been reported on word segmentation. Hence, the objective of this paper is to employ two standard existing methods to segment words of Odia handwritten documents and compare the segmentation performance of these methods with the lone Water Reservoir Algorithm available in the literature and finally rank those methods based on their segmentation performance. It is observed that out of three methods, the Tree Structure method performs the best comparing four different performance measures.

关键词： Signal processing algorithms image segmentation Character recognition Reservoirs Signal processing Embedded systems

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