This paper presents a camera orientation estimation method based on 3-line RANSAC using motion vector in a driving straight ahead vehicle. The proposed method consists of three steps: i) motion vector and z-axis vanis...
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ISBN:
(纸本)9781538630259
This paper presents a camera orientation estimation method based on 3-line RANSAC using motion vector in a driving straight ahead vehicle. The proposed method consists of three steps: i) motion vector and z-axis vanishing point estimation using feature extraction and matching, ii) line detection and classification using 3-line RANSAC algorithm, and iii) camera orientation estimation with vanishing points using classified lines. The experimental result shows proposed method effectively estimate camera orientation parameter. Therefore, the proposed method can be applied in vehicle systems for automatic driving assistance system.
Connected Component Labeling (CCL) is one of the important process in the field of imageprocessing. It can detect connected component in binary image and label them. This paper proposes a real-time single-scan CCL ar...
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Connected Component Labeling (CCL) is one of the important process in the field of imageprocessing. It can detect connected component in binary image and label them. This paper proposes a real-time single-scan CCL architecture and implementation in field-programmable gate array (FPGA) platform. This implementation has been completed on Xilinx Vertex-5 FPGA device and just used with the internal memory for storing component size and position rather than saving a whole image. It has been working at 60Hz for video of 640x480. The architecture runs in real-time while having reasonably low resource utilization, making integration with other real-time algorithms feasible.
Adequately represented indoor mapping is of great importance. For instance, the efficiency and safety of first responders gets significantly improved. Stereo SLAM algorithms achieve remarkable results, nevertheless so...
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Adequately represented indoor mapping is of great importance. For instance, the efficiency and safety of first responders gets significantly improved. Stereo SLAM algorithms achieve remarkable results, nevertheless some of their map representations have drawbacks. Point clouds can rarely be interpreted intuitively by human operators due to the absence of color and their sparsity. Nor do those point clouds represent a suitable input for possible post-processing. This paper contributes a supplementary enhancement tailored to visual SLAM algorithms. First, a method of creating dense colored point clouds is introduced, which is based on 3D reconstruction and visual SLAM algorithms. Second, a post-processing scheme is proposed, which condenses those point clouds to a blueprint-like map of the building by extracting wall segments. Evaluation is conducted on data recorded with a person-carried stereo camera setup in a typical indoor environment covering a track length of about 70 m. It is demonstrated that a dense colored point cloud has been successfully created and adds great value to intuitive interpretation by human operators. Furthermore, post-processing delivers promising results. A reliable extraction of wall segments is achieved for walls that are represented by a sufficient number of points.
Text line segmentation from handwriting image is the basis of handwriting text imageprocessing, and the accuracy of line segmentation plays a decisive role in handwriting identification, handwriting recognition, hand...
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ISBN:
(纸本)9781728113678;9781728113661
Text line segmentation from handwriting image is the basis of handwriting text imageprocessing, and the accuracy of line segmentation plays a decisive role in handwriting identification, handwriting recognition, handwriting retrieval and other research fields. The accuracy of line segmentation may directly lead to the accuracy and efficiency of handwriting identification, character recognition and text retrieval. Because offline handwriting has lost the order of writing and other information, which makes it more difficult to segment the offline handwriting image. This paper mainly aims at the complexity of the segmentation problem caused by the diversity of off-line handwriting styles, such as tilt, adhesion, overlap and so on, and compares the related solutions in recent years. In the end, some problems in line segmentation research are put forward or omitted, which is more convenient for readers to understand the field.
An optimization algorithm for image recovery is a core issue in the field of compressive sensing (CS). This paper deeply studied the CS reconstruction algorithm based on split Bregman iteration with ℓ 1 norm, which e...
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ISBN:
(纸本)9781728102481;9781728102474
An optimization algorithm for image recovery is a core issue in the field of compressive sensing (CS). This paper deeply studied the CS reconstruction algorithm based on split Bregman iteration with ℓ 1 norm, which enables the ℓ 1 norm to approximate the original ℓ 0 norm during the optimization process. Consequently, we proposed another novel algorithm improving the precision and the convergence speed based on split quadratic Bregman iteration (SQBI) with ℓ 0 norm. Besides, we analyzed its convergence by proving two monotonically decreasing theorems. Inspired by previous researches, we applied smoothed ℓ 0 norm for the optimization problem to replace the traditional ℓ 0 norm in CS. The improvement is made by using a Gaussian function to approximate the ℓ 0 norm, transforming it into a convex optimization problem, and eventually achieved a convergent solution by the steepest descent method. The experimental results show that under the same conditions, compared with other state-of-the-art algorithms, the reconstruction accuracy of the CS reconstruction algorithm based on the SQBI with smoothed ℓ 0 norm is improved significantly, and its convergence rate is also accelerated as well.
The proceedings contain 29 papers. The special focus in this conference is on Measurement, Modelling and Evaluation of Computing systems. The topics include: Evaluating a Single-Server Queue with Asynchronous Speed Sc...
ISBN:
(纸本)9783319749464
The proceedings contain 29 papers. The special focus in this conference is on Measurement, Modelling and Evaluation of Computing systems. The topics include: Evaluating a Single-Server Queue with Asynchronous Speed Scaling;Active Queue Management Based on Congestion Policing (CP-AQM);Deficit Round Robin with Limited Deficit Savings (DRR-LDS) for Fairness Among TCP Users;Modeling the Performance of ARQ Error Control in an LTE Transmission System;catching Corner Cases in Network Calculus – Flow Segregation Can Improve Accuracy;QoE Analysis of the Setup of Different Internet Services for FIFO Server systems;VirtuWind – An SDN- and NFV-Based Architecture for Softwarized Industrial Networks;A Modular Environment to Test SCADA Solutions for Wind Parks;Evaluation of Single-Hop Beaconing with Congestion Control in IEEE WAVE and ETSI ITS-G5;markov Automata on Discount!;practical QoE Evaluation of Adaptive Video Streaming;a Domain-Specific Language and Toolchain for Performance Evaluation Based on Measurements;SLA Tool;A Tool for Generating Automata of IEC60870-5-104 Implementations;a Software Tool for the Compact Solution of the Chemical Master Equation;logical PetriNet A Tool to Model Digital Circuit Petri Nets and Transform them into Digital Circuits;classCast: A Tool for Class-Based Forecasting;collider – Parallel Experiments in Silico;FunSpec4DTMC – A Tool for Modelling Discrete-Time Markov Chains Using Functional Specification;Model-Based System Design and Evaluation of imageprocessing Architectures with SimTAny Framework;markov Analysis of Optimum Caching as an Equivalent Alternative to Belady’s Algorithm Without Look-Ahead;intrusion Detection for Sequence-Based Attacks with Reduced Traffic Models;performance Benchmarking of Network Function Chain Placement algorithms.
The proceedings contain 28 papers. The special focus in this conference is on Internet and Distributed Computing systems. The topics include: Towards Island Networks: SDN-Enabled Virtual Private Networks with Peer-to-...
ISBN:
(纸本)9783030027377
The proceedings contain 28 papers. The special focus in this conference is on Internet and Distributed Computing systems. The topics include: Towards Island Networks: SDN-Enabled Virtual Private Networks with Peer-to-Peer Overlay Links for Edge Computing;almost-Fully Secured Fully Dynamic Group Signatures with Efficient Verifier-Local Revocation and Time-Bound Keys;path Planning for Multi-robot systems in Intelligent Warehouse;dynamic Framework for Reconfiguring Computing Resources in the Inter-cloud and Its Application to Genome Analysis Workflows;game-Theoretic Approach to Self-stabilizing Minimal Independent Dominating Sets;towards Social Signal Separation Based on Reconstruction Independent Component Analysis;Performance, Resilience, and Security in Moving Data from the Fog to the Cloud: The DYNAMO Transfer Framework Approach;development of a Support System to Resolve Network Troubles by Mobile Robots;a Benchmark Model for the Creation of Compute Instance Performance Footprints;towards the Succinct Representation of m Out of n;developing Agent-Based Smart Objects for IoT Edge Computing: Mobile Crowdsensing Use Case;path Planning of Robotic Fish in Unknown Environment with Improved Reinforcement Learning Algorithm;review of Swarm Intelligence algorithms for Multi-objective Flowshop Scheduling;exploiting Long Distance Connections to Strengthen Network Robustness;an Online Adaptive Sampling Rate Learning Framework for Sensor-Based Human Activity Recognition;a Secure Video-Based Robust and Aesthetic 2D Barcode;a Migratable Container-Based Replication Management for Inter-cloud;Dilated Deep Residual Network for Post-processing in TPG Based image Coding;underground Intelligent Logistic System Integrated with Internet of Things;extending the Advisor Concept to Deal with Known-Ahead Transportation Tasks;a Framework for Task-Guided Virtual Machine Live Migration.
Electrical measurement of degradation in metal films induced by high thermo-mechanical stress is not possible. Therefore, different imaging methods are used in practice to visualize the changes in material microstruct...
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ISBN:
(纸本)9781728102481;9781728102474
Electrical measurement of degradation in metal films induced by high thermo-mechanical stress is not possible. Therefore, different imaging methods are used in practice to visualize the changes in material microstructure. In this work, SEM (Scanning Electron Microscopy) cross section images of the metal layer of interest that illustrate the fatigue induced degradation and material microstructure are analyzed. We propose an unsupervised algorithm for detection and quantitative assessment of the damage in mentioned images. In the first stage of the algorithm, the metal layer of interest is extracted from the background using k-Means method. In the second stage, the non-local means (NL-means) denoising method with automatically computed standard noise deviation followed by post-processing and k-Means is used to detect the damage patterns. Visual and quantitative evaluation of results reveals that the algorithm provides robust and plausible results.
Modern collision avoidance systems implemented into the Intelligent Transportation systems work on the base of the image information analysis. For the control of unintentional departure from the lane, the vehicles in ...
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ISBN:
(数字)9783319662510
ISBN:
(纸本)9783319662510;9783319662503
Modern collision avoidance systems implemented into the Intelligent Transportation systems work on the base of the image information analysis. For the control of unintentional departure from the lane, the vehicles in Cooperative-intelligent Transportation systems use surveillance systems-Lane Departure Warning. A very important parameter of these systems is the reliability of the method of digital image information processing, which depends on the choice of the optimum algorithm for the detection of road markings in different light conditions. The parameters of imageprocessingalgorithms should be set on the base of software simulation with real collected traffic data. The contribution is focused on finding and testing effective methods of digital imageprocessingalgorithms to monitoring the crossing of lane with a focus on reliability evaluation.
While the popularity of high-resolution, computer-vision applications (e.g. mixed reality, autonomous vehicles) is increasing, there have been complementary advances in time-of-flight depth sensor resolution and quali...
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ISBN:
(纸本)9781728102481;9781728102474
While the popularity of high-resolution, computer-vision applications (e.g. mixed reality, autonomous vehicles) is increasing, there have been complementary advances in time-of-flight depth sensor resolution and quality. These advances in time-of-flight sensors provide a platform for new research into real-time, depth-upsampling algorithms targeted at high-resolution video systems with low-latency requirements. This paper describes a case study in which a previously developed bilateral-filter-style upsampling algorithm is profiled, parallelized, and accelerated on an FPGA using high-level synthesis tools from Xilinx. We show that our accelerated algorithm can effectively upsample the resolution and reduce the noise of time-of-flight sensors. We also demonstrate that this algorithm exceeds the real-time requirements of 90 frames per second necessitated by mixed-reality hardware, achieving a lower-bound speedup of 40 times over the fastest CPU-only version.
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