Real time hardware co-simulation of Edge Detection for video processing system

2012 ◽  
Author(s):  
Yahia Said ◽  
Taoufik Saidani ◽  
Fethi Smach ◽  
Mohamed Atri
Keyword(s):  
Edge Detection ◽  
Real Time ◽  
Video Processing ◽  
Processing System

Design of a real-time video processing system with FPGA

2002 ◽  
Author(s):  
Wei Liu ◽  
Zeying Chi ◽  
Wenjian Chen
Keyword(s):  
Real Time ◽  
Video Processing ◽  
Processing System

The Design of Real-Time and High-Speed Video Processing Platform for Aerial UAV Based on DM642

2014 ◽  
Vol 1061-1062 ◽  
pp. 1186-1189
Author(s):  
Ming Zhe Wei ◽  
Wan Wei Tang
Keyword(s):  
Real Time ◽  
Video Processing ◽  
High Speed ◽  
Rapid Development ◽  
Processing System ◽  
Video Signal ◽  
Good Effect ◽  
Time Data ◽  
Spatial Interference ◽  
On Chip

With the rapid development of aerial UAV (Unmanned Aerial Vehicle), the design of real-time data acquisition and transmission system for the video signal has a new applied field. It is different from traditional video acquisition and processing system, aerial video signal has the problems of screen jitter and spatial interference. The processing algorithm of aerial UAV airborne video signal is put forward in the paper, and the platform of high speed procession is constructed based on chip TMS320DM642, and get a good effect.

scholarly journals FPGA-Based Stereo-Vision System Mimicking Human Binocular Vision

2021 ◽  
Author(s):  
Gvarami Labartkava
Keyword(s):  
Real Time ◽  
Binocular Vision ◽  
Video Processing ◽  
High Performance ◽  
Moving Objects ◽  
Peripheral Vision ◽  
Vision System ◽  
Processing System ◽  
Object Motion ◽  
Human Vision

Human vision is a complex system which involves processing frames and retrieving information in a real-time with optimization of the memory, energy and computational resources usage. It can be widely utilized in many real-world applications from security systems to space missions. The research investigates fundamental principles of human vision and accordingly develops a FPGA-based video processing system with binocular vision, capable of high performance and real-time tracking of moving objects in 3D space. The undertaken research and implementation consist of: 1. Analysis of concepts and methods of human vision system; 2. Development stereo and peripheral vision prototype of a system-on-programmable chip (SoPC) for multi-object motion detection and tracking; 3. Verification, test run and analysis of the experimental results gained on the prototype and associated with the performance constraints; The implemented system proposes a platform for real-time applications which are limited in current approaches.

scholarly journals Energy-Efficient NoC-Based Systems for Real-Time Multimedia Applications using Approximate Computing

2021 ◽  
Author(s):  
Wagner I. Penny ◽  
Daniel M. Palomino ◽  
Marcelo S. Porto ◽  
Bruno Zatt
Keyword(s):  
Real Time ◽  
Video Processing ◽  
Energy Efficient ◽  
Processing System ◽  
Schedulability Analysis ◽  
Multimedia Applications ◽  
Timing Constraints ◽  
Approximate Computing ◽  
Processing Elements ◽  
Fractional Motion Estimation

This work presents an energy-efficient NoC-based system for real-time multimedia applications employing approximate computing. The proposed video processing system, called SApp-NoC, is efficient in both energy and quality (QoS), employing a scalable NoC architecture composed of processing elements designed to accelerate the HEVC Fractional Motion Estimation (FME). Two solutions are proposed: HSApp-NoC (Heuristc-based SApp-NoC), and MLSApp-NoC (Machine Learning-based SApp-NoC). When compared to a precise solution processing 4K videos at 120 fps, HSApp-NoC and MLSApp-NoC reduce about 48.19% and 31.81% the energy consumption, at small quality reduction of 2.74% and 1.09%, respectively. Furthermore, a set of schedulability analysis is also proposed in order to guarantee the meeting of timing constraints at typical workload scenarios.

Accelerating Sobel Edge Detection Using Compressor Cells Over FPGAs

2018 ◽  
pp. 1133-1154
Author(s):  
Ahmed Abouelfarag ◽  
Marwa Ali Elshenawy ◽  
Esraa Alaaeldin Khattab
Keyword(s):  
Edge Detection ◽  
Real Time ◽  
Video Processing ◽  
High Level Synthesis ◽  
Computational Time ◽  
The Novel ◽  
Image And Video Processing ◽  
Sobel Edge Detection ◽  
High Level ◽  
Time Image

Recently, computer vision is playing an important role in many essential human-computer interactive applications, these applications are subject to a “real-time” constraint, and therefore it requires a fast and reliable computational system. Edge Detection is the most used approach for segmenting images based on changes in intensity. There are various kernels used to perform edge detection, such as: Sobel, Robert, and Prewitt, upon which, the most commonly used is Sobel. In this research a novel type of operator cells that perform addition is introduced to achieve computational acceleration. The novel operator cells have been employed in the chosen FPGA Zedboard which is well-suited for real-time image and video processing. Accelerating the Sobel edge detection technique is exploited using different tools such as the High-Level Synthesis tools provided by Vivado. This enhancement shows a significant improvement as it decreases the computational time by 26% compared to the conventional adder cells.

Accelerating Sobel Edge Detection Using Compressor Cells Over FPGAs

2017 ◽  
pp. 1-21
Author(s):  
Ahmed Abouelfarag ◽  
Marwa Ali Elshenawy ◽  
Esraa Alaaeldin Khattab
Keyword(s):  
Edge Detection ◽  
Real Time ◽  
Video Processing ◽  
High Level Synthesis ◽  
Computational Time ◽  
The Novel ◽  
Image And Video Processing ◽  
Sobel Edge Detection ◽  
High Level ◽  
Time Image

Recently, computer vision is playing an important role in many essential human-computer interactive applications, these applications are subject to a “real-time” constraint, and therefore it requires a fast and reliable computational system. Edge Detection is the most used approach for segmenting images based on changes in intensity. There are various kernels used to perform edge detection, such as: Sobel, Robert, and Prewitt, upon which, the most commonly used is Sobel. In this research a novel type of operator cells that perform addition is introduced to achieve computational acceleration. The novel operator cells have been employed in the chosen FPGA Zedboard which is well-suited for real-time image and video processing. Accelerating the Sobel edge detection technique is exploited using different tools such as the High-Level Synthesis tools provided by Vivado. This enhancement shows a significant improvement as it decreases the computational time by 26% compared to the conventional adder cells.

scholarly journals Real Time Sobel Edge Detection Based on Reconfigurable Computing

2020 ◽  
Vol 8 (5) ◽  
pp. 2466-2468
Keyword(s):  
Edge Detection ◽  
Real Time ◽  
Video Processing ◽  
Reconfigurable Computing ◽  
Crack Detection ◽  
Traffic Monitoring ◽  
Lane Detection ◽  
Verilog Hdl ◽  
Detection Algorithms ◽  
Sobel Edge Detection

Edge detection is a fundamental operation in many image and video processing applications. It is used in various fields like industries, aerospace, surveillance, medical fields, traffic monitoring system, lane detection, driverless vehicles, crack detection in roads and several other applications. Most of the edge detection algorithms are software based but in real time applications these are not efficient hence in this paper we have explored about Hardware platform. The reason for selecting Sobel edge detection operator is it incorporates both the edge detection and a smoothing operator to provide good edge detection capability in noisy environment. This design uses Verilog HDL language for design and Vivado is used for simulation.

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