Reconfiguration of Distributed Information Fusion System ? A case study

Information Fusion Systems are now widely used in different fusion contexts, like scientific processing, sensor networks, video and image processing. One of the current trends in this area is to cope with distributed systems. In this context, we have defined and implemented a Dynamic Distributed Information Fusion System runtime model. It allows us to cope with dynamic execution supports while trying to maintain the functionalities of a given Dynamic Distributed Information Fusion System. The paper presents our system, the reconfiguration problems we are faced with and our solutions.Comment: 6 pages - Preprint versio

Movers and shakers: Granular damping in microgravity

The response of an oscillating granular damper to an initial perturbation is studied using experiments performed in microgravity and granular dynamics mulations. High-speed video and image processing techniques are used to extract experimental data. An inelastic hard sphere model is developed to perform simulations and the results are in excellent agreement with the experiments. The granular damper behaves like a frictional damper and a linear decay of the amplitude is bserved. This is true even for the simulation model, where friction forces are absent. A simple expression is developed which predicts the optimal damping conditions for a given amplitude and is independent of the oscillation frequency and particle inelasticities.Comment: 9 pages, 9 figure

Synthetic Image Detection: Highlights from the IEEE Video and Image Processing Cup 2022 Student Competition

The Video and Image Processing (VIP) Cup is a student competition that takes place each year at the IEEE International Conference on Image Processing. The 2022 IEEE VIP Cup asked undergraduate students to develop a system capable of distinguishing pristine images from generated ones. The interest in this topic stems from the incredible advances in the AI-based generation of visual data, with tools that allows the synthesis of highly realistic images and videos. While this opens up a large number of new opportunities, it also undermines the trustworthiness of media content and fosters the spread of disinformation on the internet. Recently there was strong concern about the generation of extremely realistic images by means of editing software that includes the recent technology on diffusion models. In this context, there is a need to develop robust and automatic tools for synthetic image detection

Aplikasi Deteksi Tepi pada Realtime Video Menggunakan Algoritma Canny Detection

Real-time video and image processing is used in a wide variety of applications from video surveillance and traffic management to medical imaging applications. This paper presents the implementation of an canny edge-detection using in realtime video from camera. The Canny algorithm uses an optimal edge detector based on a set of criteria which include finding the most edges by minimizing the error rate, marking edges as closely as possible to the actual edges to maximize localization, and marking edges only once when a single edge exists for minimal response

Using Manual Measurements on Event Recorder Video and Image Processing Algorithms to Extract Optical Parameters and Range

Vehicle kinematics and optical parameters such as optical angle, optical expansion rate, and tau are thought to underlie drivers’ ability to avoid and handle critical traffic situations. Analyses of these parameters in naturalistic driving data with video, such as commercial event recordings of near-crashes and crashes, can provide insight into driver behavior in critical traffic situations. This paper describes a pair of methods, one for the range to a lead vehicle and one for its optical angle, that are derived from image processing mathematics and that provide driver behavior researchers with a relatively simple way to extract optical parameters from video-based naturalistic data when automatic image processing is not possible. The methods begin with manual measurements of the size of other road users on a video on a screen. To develop the methods, 20 participants manually measured the width of a lead vehicle on 14 images where the lead vehicle was placed at different distances from the camera. An on-market DriveCam Event Recorder was used to capture these images. A linear model that corrects distortion and modeling optics was developed to transform the on-screen measurements distance (range) to and optical angle of the vehicle. The width of the confidence interval for predicted range is less than 0.1m when the actual distance is less than 10m and the lead-vehicle width estimate is correct. The methods enable driver behavior researchers to easily and accurately estimate useful kinematic and optical parameters from videos (e.g., of crashes and nearcrashes) in event-based naturalistic driving data

Transient, Non-Axisymmetric Modes in Instability of Unsteady Circular Couette Flow

Laboratory and numerical experiments were conducted to quantitatively determine the modal structure of transient, nonaxisymmetric modes observed during the instability of an impulsively initiated circular‐Couette flow. The instability develops initially as an axisymmetric, Görtler‐vortex state and persists ultimately as a steady, axisymmetric Taylor‐vortex state of different wavelength. The transition between these two states results from the instability of the Görtler mode combined with the underlying developing swirl flow and is dominated by nonaxisymmetric modes. The laboratory experiments employed flow visualization coupled with digital video and image‐processing techniques; numerical experiments were performed using the spectral‐element code

Real-Time Edge Detection using Sundance Video and Image Processing System

Edge detection from images is one of the most important concerns in digital image and video processing. With development in technology, edge detection has been greatly benefited and new avenues for research opened up, one such field being the real time video and image processing whose applications have allowed other digital image and video processing. It consists of the implementation of various image processing algorithms like edge detection using sobel, prewitt, canny and laplacian etc. A different technique is reported to increase the performance of the edge detection. The algorithmic computations in real-time may have high level of time based complexity and hence the use of Sundance Module Video and Image processing system for the implementation of such algorithms is proposed here. In this module is based on the Sundance module SMT339 processor is a dedicated high speed image processing module for use in a wide range of image analysis systems. This processor is combination of the DSP and FPGA processor. The image processing engine is based upon the „Texas Instruments‟ TMS320DM642 Video Digital Signal Processor. And A powerful Vitrex-4 FPGA (XC4VFX60-10) is used onboard as the FPGA processing unit for image data. It is observed that techniques which follow the stage process of detection of noise and filtering of noisy pixels achieve better performance than others. In this thesis such schemes of sobel, prewitt, canny and laplacian detector are proposed

Real-Time UAV Pose Estimation and Tracking Using FPGA Accelerated April Tag

April Tags and other passive fiducial markers are widely used to determine localization using a monocular camera. It utilizes specialized algorithms that detect markers to calculate their orientation and distance in three dimensional (3-D) space. The video and image processing steps performed to use these fiducial systems dominate the computation time of the algorithms. Low latency is a key component for the real-time application of these fiducial markers. The drawbacks of performing the video and image processing in software is the difficulty in performing the same operation in parallel effectively. Specialized hardware instantiations with the same algorithm scan efficiently parallelize them as well as operate on the image in a streaming fashion. Compared to graphics processing units (GPUs) that also perform well in the field, field programmable gate arrays (FPGAs) operate with less power, making them optimal with tight power constraints. This research describes such an optimization for the April Tag algorithm on an unmanned aerial vehicle with an embedded platform to perform real-time pose estimation, tracking, and localization in GPS-denied (global positioning system) environments at 30 frames per second (FPS) by converting the initial embedded C/C++ solution to a heterogeneous one through hardware acceleration. It compares the size, accuracy, and speed of the April Tag algorithm’s various implementations. The initial solution operated at around 2 FPS while the final solution, a novel heterogeneous algorithm on the Fusion 2 Zynq 7020 system on chip (SoC), operated at around 43 FPS using hardware acceleration. The research proposes a pipeline that breaks the algorithm into distinct steps where portions of it can be improved by utilizing algorithms optimized to run on a FPGA. Additional steps were made to further reduce the hardware algorithm’s resource utilization. Each step in the software was compared against its hardware counterpart using its utilization and timing as benchmarks

Web 2.0 virtual design studio : social networking as facilitator of design education

In 2009, Deakin University and the Chinese University of Hong Kong trailed the use of Web 2.0 technologies to enhance learning outcomes in a third-year architectural design studio that was modelled on the virtual design studios (VDSs) of the past decades. The studio developed the VDS further by integrating a social learning environment into the blended learning experience. The Web 2.0 VDS utilized the social networking site Ning.com, YouTube, Skype and various three-dimensional modelling, video and image processing, and chat software to deliver lectures, communicate learning goals, disseminate learning resources, submitting, providing feedback and comments to various design works, and assessing of students’ outcomes. This research centres on issues of learning and teaching associated with the development of a social network VDS