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

共 15550 条记录，以下是4991-5000 订阅

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Perceptual Hashing For Efficient Fingerprint Based Identification 4

Perceptual Hashing For Efficient Fingerprint Based Identific...

引用

4th International conference on Advanced Computing and Communication systems (ICACCS)

作者： Muthu, Rajesh Rani, C. VIT Univ Sch Elect Engn Vellore Tamil Nadu India

ISBN: (纸本)9781509045594

This paper proposes the use of perceptual hashing to improve minutiae extraction of fingerprint images that tolerates context-preserving operations. The hash extraction is performed after wavelet transform and singular value decomposition (SVD). The performance evaluation of this approach has been assessed using various metrics such as SSIM and PSNR. Experimentally, it has shown robustness against image processing operations and geometric attacks.

关键词： Estimation Field programmable gate arrays OFDM Modulation Filtration Clocks Signal processing algorithms

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Energy Consumption and Data Amount Reduction Using Object Detection on Embedded Platform 7th

Energy Consumption and Data Amount Reduction Using Object De...

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7th EAI International conference on Sensor systems and Software (S-CUBE)

作者： Snajder, Boris Kalafatic, Zoran Bilas, Vedran Univ Zagreb Fac Elect Engn & Comp Zagreb Croatia

ISBN: (纸本)9783319615639;9783319615622

High resolution image handling often results with high energy burden for battery-powered devices, such as sensor nodes in WSN. Motivation for this study is assessment of energy consumption of the sensor node with high-resolution camera, featuring image processing. We present a selection of object detection algorithms and evaluate their efficiency. To verify applicability of those algorithms, we acquired image sequence that correspond to applications of pests detection in agriculture. We verified considered algorithms' performances: recall, precision and expected reduction of the data amount. Energy required to execute considered algorithms was measured on ARM processor based platform. Our results show that object extraction on a node can provide reduction of the data amount by up to three orders of magnitude. While simple algorithms can lead to lower overall energy consumption of the node, the more complex algorithm provides better performances, but at a cost of prohibitively high energy consumption.

关键词： Wireless sensor networks Energy efficiency image processing Object detection Data amount reduction

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Component-Based Distributed Framework for Coherent and Real-Time video Dehazing 20

Component-Based Distributed Framework for Coherent and Real-...

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20th IEEE International conference on Computational Science and Engineering (CSE) / 15th IEEE/IFIP International conference on Embedded and Ubiquitous Computing (EUC)

作者： Wang, Meihua Mai, Jiaming Liang, Yun Cai, Ruichu Zhengjia, Tom Zhang, Zhenjie South China Agr Univ Coll Math & Informat Guangzhou Guangdong Peoples R China Guangdong Univ Technol Sch Comp Sci & Technol Guangzhou Guangdong Peoples R China Illinois Singapore Pte Ltd Adv Digital Sci Ctr Singapore Singapore

ISBN: (纸本)9781538632215

Traditional dehazing techniques, as a well-studied topic in image processing, are now widely used to eliminate the haze effects from individual images. However, even the state-of-the-art dehazing algorithms may not provide sufficient support to video analytics, as a crucial pre-processing step for video-based decision making systems (e.g., robot navigation), due to the limitations of these algorithms on poor result coherence and low processing efficiency. This paper presents a new framework, particularly designed for video dehazing, to output coherent results in real time, with two novel techniques. We decompose the dehazing algorithms into three generic components, namely transmission map estimator, atmospheric light estimator and haze-free image generator. They can be simultaneously processed by multiple threads in the distributed system, such that the processing efficiency is optimized by automatic CPU resource allocation based on the workloads. The combination of these techniques enables our framework to generate highly consistent and accurate dehazing results in real-time, by using only 3 PCs connected by Ethernet.

关键词： video dehazing image restoration image enhancement

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Application of System on Chip (SoC) Devices for the Design of a Smoke Detector Working with Megapixel image Streams 22

Application of System on Chip (SoC) Devices for the Design o...

引用

22nd International conference on Methods and Models in Automation and Robotics (MMAR)

作者： Pamula, Wieslaw Sajkowski, Maciej Stenzel, Tomasz Michalak, Jaroslaw Baron, Grzegorz Szady, Bartlomiej Silesian Tech Univ Fac Transport Dept Transport Syst & Traff Engn Katowice Poland Silesian Tech Univ Fac Elect Engn Dept Power Elect Elect Drives & Robot Gliwice Poland Silesian Tech Univ Fac Automat Control Elect & Comp Sci Inst Informat Gliwice Poland

ISBN: (纸本)9781538624029

The paper discusses the application of System on Chip devices for processing Megapixel video streams. The domain of image processing using high resolution images is very demanding in the scope of calculating power and frequently exploits special processing hardware. The progress of integration technology brings about SoC which are capable of meeting such processing demands. Characteristics of FPGA and DSP based systems are assessed. A concise survey of chip solutions is presented and a pair of representative systems is chosen for comparison of their properties. The design of a smoke detection system is used for evaluating the advantages and drawbacks of using such SoC solutions. Almost identical image processing algorithms are implemented in the case of FPGA and DSP. Both solutions meet the image processing requirements and are suitable for real time processing. FPGA based solution is much faster as it uses pipelining for improving the utilisation of scarce memory resources.

关键词： SoC image processing high resolution images FPGA DSP smoke detection

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Scalable image Tamper Detection and Recovery Based on Dual-Rate Source-Channel Coding 3

Scalable Image Tamper Detection and Recovery Based on Dual-R...

引用

3rd Iranian conference on Signal processing and Intelligent systems (ICSPIS)

作者： Daneshmandpour, Navid Danyali, Habibollah Helfroush, Mohammad Sadegh Shiraz Univ Technol Dept Elect & Elect Engn Shiraz Iran

ISBN: (纸本)9781538649725

In image tamper detection and recovery methods prevalently two sets of data need to be embedded into the main image, one known as authentication data for tamper detection and the other known as reference data for tamper recovery. In this paper, a scalable method for image tamper detection and recovery based on a dual-rate source-channel coding is proposed. In the proposed method the original image is first compressed by a scalable source coding algorithm. The compressed bitstream is then partitioned into two parts. Both parts are protected with a channel coding algorithm but with two different rates according to their importance for tamper recovery process. The proposed method takes advantage of two state-of-the-art algorithms, SPIRT for source coding and LDPC for channel coding. Simulation results show a noticeable improvement compared with related tamper detection and recovery schemes in the literature. Besides the reconstruction quality of the recovered image is scalable. This means that in low tampering rates, high-quality images are recovered and in high tampering rates, the image is still recoverable but with less reconstruction quality. Therefore the proposed method succeeded to both recover higher tampering rates and preserve the image quality.

关键词： Tamper Detection and Recovery Source-channel coding SPIHT LDPC

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Optimising Quality-of-Control for Data-Intensive Multiprocessor image-Based Control systems Considering Workload Variations

Optimising Quality-of-Control for Data-Intensive Multiproces...

引用

Euromicro Symposium on Digital System Design

作者： Sajid Mohamed Diqing Zhu Dip Goswami Twan Basten Electronic systems Group Eindhoven University of Technology The Netherlands

ISBN: (纸本)9781538673782

image-Based Control (IBC) systems have a long sample period. Sensing in these systems consists of compute-intensive image processing algorithms whose response times are dependent on image workload. IBC systems are typically designed for the worst-case workload that results in a long sample period and hence suboptimal quality-of-control (QoC). This worst-case based design is further considered for mapping of controller tasks and allocating platform resources, resulting in significant resource over-provisioning. Our design philosophy is to sample as fast as possible to optimise QoC for a given platform allocation, and for this, we present a structured design flow. Workload variations determine how fast we can sample and we model this dynamic behaviour using the concept of workload scenarios. Our choice of scenario-aware dataflow as the formal model for our application enables us to: i) model dynamic behaviour, analyse timing, and optimally map application tasks to the platform for maximising the effective utilisation of allocated resources, ii) relate throughput of the dataflow graph to the sample period, and thus combine dataflow analysis and mapping with control design parameters and QoC to identify system scenarios, and iii) to efficiently implement a run-time mechanism that manages necessary dynamic reconfiguration between system scenarios. Our results show that our design approach outperforms the worst-case based design with respect to optimising QoC and maximising effective resource utilisation.

关键词： Task analysis Analytical models Resource management Computational modeling Cameras image processing

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Optimized Multi-Shaped Traffic Light Detection and Signal Recognition with Guided Framework

Optimized Multi-Shaped Traffic Light Detection and Signal Re...

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International conference on Advances in ICT for Emerging Regions

作者： R.P.U.N. Rajapaksha L. Ranathunga Department of Information Technology University of Moratuwa University of Moratuwa Katubedda Sri Lanka

ISBN: (纸本)9781538673539;9781538673522

Traffic Light detection and recognition has become one of the critical research areas when it comes to autonomous driving vehicles. Developing an algorithm to detect different shaped traffic lights such as traffic lights (TLs) with arrowheads, circular shapes, horizontally and vertically oriented TLs and TLs in different illumination conditions during daytime still remains a challenge. This paper evaluates the existing algorithms, which uses heuristic or template matching based image processing methods and other learning based systems, that consumes higher time and processing power for training and map based systems and proposes a novel optimized algorithm using machine vision techniques to meet those challenges. The experiments were carried out using videos taken by front camera of vehicles. The results of the algorithm show a higher accuracy for precision and recall evaluations.

关键词： Shape image color analysis Cameras Brightness videos Lighting Global Positioning System

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SRIANN: SPHERE RING INTERSECTION FOR APPROXIMATE NEAREST NEIGHBOR SEARCH IN viDEOS

SRIANN: SPHERE RING INTERSECTION FOR APPROXIMATE NEAREST NEI...

引用

IEEE International conference on image processing

作者： Yi-Ting Chen Wei-Chih Tu Shao-Yi Chien Graduate Institute of Electronics Engineering National Taiwan University

In the field of approximate nearest neighbor (ANN) search, rare of the existing approaches are tailored for video applications. The Ring Intersection Approximate Nearest Neighbor (RIANN) is the first ANN search algorithm for videos. It achieves real-time by performing the ANN search on the sparse grid and interpolating others. For some applications, the dense ANN search is needed to ensure the searching accuracy. To achieve dense ANN search in real-time, we consider the parallel computing as a solution. However, the RIANN algorithm is not suitable for parallel computing as the algorithm itself suffers from bad thread coherency. In this paper, we propose the Sphere Ring Intersection Approximate Nearest Neighbor (SRIANN), which solves the problem of bad thread coherency and improves the accuracy of ANN search compared to the original RIANN method. The experimental results show that the proposed method is the only one able to perform dense ANN search for CIF videos in real-time.

关键词： Instruction sets videos Graphics processing units Real-time systems Databases Approximation algorithms Parallel processing

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A Neuromorphic Approach To image processing And Machine vision 4

A Neuromorphic Approach To Image Processing And Machine Visi...

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4th International conference on image Information processing (ICIIP)

作者： Subramaniam, Arvind Birla Inst Technol & Sci BITS Pilani Hyderabad Campus Hyderabad Andhra Pradesh India

ISBN: (纸本)9781509067343

Neuromorphic engineering is essentially the development of artificial systems, such as electronic analog circuits that employ information representations found in biological nervous systems. Despite being faster and more accurate than the human brain, computers lag behind in recognition capability. However, it is envisioned that the advancement in neuromorphics, pertaining to the fields of computer vision and image processing will provide a considerable improvement in the way computers can interpret and analyze information. In this paper, we explore the implementation of visual tasks such as image segmentation, visual attention and object recognition. Moreover, the concept of anisotropic diffusion has been examined followed by a novel approach employing memristors to execute image segmentation. Additionally, we have discussed the role of neuromorphic vision sensors in artificial visual systems and the protocol involved in order to enable asynchronous transmission of signals. Moreover, two widely accepted algorithms that are used to emulate the process of object recognition and visual attention have also been discussed. Throughout the span of this paper, we have emphasized on the employment of non-volatile memory devices such as memristors to realize artificial visual systems. Finally, we discuss about hardware accelerators and wish to represent a case in point for arguing that progress in computer vision may benefit directly from progress in non-volatile memory technology.

关键词： Object recognition Memristor image segmentation Neuromorphic vision sensors Address Event Representation Random walker algorithm Anisotropic Diffusion Dynamic vision Sensor

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A vision Based Positioning Gas Leakage Test Automation System

A Vision Based Positioning Gas Leakage Test Automation Syste...

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International conference on Control, Engineering & Information Technology (CEIT)

作者： Akın İlker Savran Tufan Kumbasar Arçelik Tumble Dryer Plant Tekirdag Turkey Control and Automation Engineering Department Istanbul Technical University Istanbul Turkey

ISBN: (纸本)9781538676424

The automation project with vision based positioning by using ABB IRB 140 robot is proposed, the coordinate transformation and camera calibration is applied, two types gas leakage test for HP dryers are proposed and the image processing algorithms for welding points of gas leakage test by dividing three areas of chassis are proposed. For this purpose, the robotic automation system has been installed and the real-time experimental studies are performed to show the effectiveness of the vision based positioning ABB IRB 140 robot for the gas leakage test by presentation the derivations of welding points positions.

关键词： Robot kinematics Welding Cameras Service robots image processing Robot vision systems

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