Real-time video processing in ZedBoard
Video processing is a technique that is widely used nowadays to meet the growing demands in the industry. By implementing a video processing system into a real-time operating system, it can be used in many ways such as mounting it on top of a drone to carry out search and rescue mission or for mi...
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sg-ntu-dr.10356-703232023-03-03T20:34:39Z Real-time video processing in ZedBoard Chua, Ivan Rui Xiang Arvind Easwaran School of Computer Science and Engineering DRNTU::Engineering::Computer science and engineering::Hardware::Input/output and data communications Video processing is a technique that is widely used nowadays to meet the growing demands in the industry. By implementing a video processing system into a real-time operating system, it can be used in many ways such as mounting it on top of a drone to carry out search and rescue mission or for military usage, etc. During this operation, the video feed must be able to display the real-time scenario within a limited amount of time. Time is an essential and critical role in such operation. Thus, the system is required to complete all its operation within the given time frame. In this project, we focus on evaluating a hybrid processing platform such as Zynq 7000 (e.g. Avnet Zedboard) which comprise of both Commercial-Off-The-Shelf (COTS) processor (ARM) and Field Programmable Gate Array (FPGA) for a video processing real-time system. This report investigates the design of video processing system on FPGA and compares it against the implementation on a COTS processor. We integrate a low-cost Video Graphics Array (VGA) camera with Avnet Zedboard and implement a simple edge detection system on the FPGA. To evaluate the performance of our implementation, we implement the same system on Raspberry Pi (RPi) which comes with ARM Cortex-A7 processor. It is found that the performance of the video processing system implemented on FPGA is superior in comparison to that of COTS processor implementation. The comparison results show that FPGA has a much high frame per second (fps) than the ARM processor when processing video process operation. Bachelor of Engineering (Computer Engineering) 2017-04-19T08:52:39Z 2017-04-19T08:52:39Z 2017 Final Year Project (FYP) http://hdl.handle.net/10356/70323 en Nanyang Technological University 40 p. application/pdf |
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DRNTU::Engineering::Computer science and engineering::Hardware::Input/output and data communications Chua, Ivan Rui Xiang Real-time video processing in ZedBoard |
description |
Video processing is a technique that is widely used nowadays to meet the growing demands
in the industry. By implementing a video processing system into a real-time operating system, it
can be used in many ways such as mounting it on top of a drone to carry out search and rescue
mission or for military usage, etc. During this operation, the video feed must be able to display the
real-time scenario within a limited amount of time. Time is an essential and critical role in such
operation. Thus, the system is required to complete all its operation within the given time frame.
In this project, we focus on evaluating a hybrid processing platform such as Zynq 7000
(e.g. Avnet Zedboard) which comprise of both Commercial-Off-The-Shelf (COTS) processor
(ARM) and Field Programmable Gate Array (FPGA) for a video processing real-time system. This
report investigates the design of video processing system on FPGA and compares it against the
implementation on a COTS processor.
We integrate a low-cost Video Graphics Array (VGA) camera with Avnet Zedboard and
implement a simple edge detection system on the FPGA. To evaluate the performance of our
implementation, we implement the same system on Raspberry Pi (RPi) which comes with ARM
Cortex-A7 processor. It is found that the performance of the video processing system implemented
on FPGA is superior in comparison to that of COTS processor implementation.
The comparison results show that FPGA has a much high frame per second (fps) than the
ARM processor when processing video process operation. |
author2 |
Arvind Easwaran |
author_facet |
Arvind Easwaran Chua, Ivan Rui Xiang |
format |
Final Year Project |
author |
Chua, Ivan Rui Xiang |
author_sort |
Chua, Ivan Rui Xiang |
title |
Real-time video processing in ZedBoard |
title_short |
Real-time video processing in ZedBoard |
title_full |
Real-time video processing in ZedBoard |
title_fullStr |
Real-time video processing in ZedBoard |
title_full_unstemmed |
Real-time video processing in ZedBoard |
title_sort |
real-time video processing in zedboard |
publishDate |
2017 |
url |
http://hdl.handle.net/10356/70323 |
_version_ |
1759855057700913152 |