Welcome To UTPedia

We would like to introduce you, the new knowledge repository product called UTPedia. The UTP Electronic and Digital Intellectual Asset. It stores digitized version of thesis, dissertation, final year project reports and past year examination questions.

Browse content of UTPedia using Year, Subject, Department and Author and Search for required document using Searching facilities included in UTPedia. UTPedia with full text are accessible for all registered users, whereas only the physical information and metadata can be retrieved by public users. UTPedia collaborating and connecting peoples with university’s intellectual works from anywhere.

Disclaimer - Universiti Teknologi PETRONAS shall not be liable for any loss or damage caused by the usage of any information obtained from this web site.Best viewed using Mozilla Firefox 3 or IE 7 with resolution 1024 x 768.

Video Object Avoidance Implementation on Embedded Platform

Keat, Yeong Ming (2015) Video Object Avoidance Implementation on Embedded Platform. IRC, Universiti Teknologi PETRONAS. (Unpublished)

Download (2459Kb) | Preview


Motion detection is fundamental in various computer vision related applications. In this project, there are two motion detection techniques being studied, namely optical flow and motion templates. This is to detect the moving obstacles as well as to classify the direction of the moving obstacles. Optical flow is the computation to approximate the image motion, while motion templates use the motionhistory- image (MHI) to keep track of the most recent movement with the timestamp. Besides, this project also covers the static object detection, where HSV color model classification technique is used to detect the static obstacles. This technique is based on filtration of color, which depending on the HSV values of the static objects. Both motion and static detection algorithms will be tested in Window Visual Studio 2010, before implementing them into the embedded platform, which is Raspberry Pi. Meanwhile, OpenCV is used as the computer vision library throughout the project. At the end of this project object, motion templates is selected as a more suitable motion detection techniques due to its extra information, which is the angle. The HSV technique can detect the static objects but limited to the calibrated color only

Item Type: Final Year Project
Academic Subject : Academic Department - Electrical And Electronics - Pervasisve Systems - Digital Electronics - Design
Divisions: Engineering > Electrical and Electronic
Depositing User: Ahmad Suhairi Mohamed Lazim
Date Deposited: 27 Aug 2015 16:30
Last Modified: 25 Jan 2017 09:36
URI: http://utpedia.utp.edu.my/id/eprint/15565

Actions (login required)

View Item View Item

Document Downloads

More statistics for this item...