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.

REAL-TIME OBSTACLE DETECTION USING SMART IMAGING FOR NAVIGATION OF AUTONOMOUS SMALL VESSEL

HASANE, ABDUL HAKIM (2019) REAL-TIME OBSTACLE DETECTION USING SMART IMAGING FOR NAVIGATION OF AUTONOMOUS SMALL VESSEL. IRC, Universiti Teknologi PETRONAS. (Submitted)

[img] PDF
Restricted to Registered users only

Download (6Mb)

Abstract

The world has moving toward unmanned machinery in many areas nowadays. The experts and scientists have gather around the world to jump into this new kind of technology development. All the technologies involve in making autonomous or unmanned machine can be very complicated as the machine need to be working using their own artificial brain without human interruption. This artificial brain or called as deep neural network is the most important part in making an autonomous machine working successfully on their own. In industrial area, there are several tasks which had been done by human before been replaced by these autonomous or unmanned mechanical robot. The heavier or tougher task could be replaced by unmanned machine to increase production rate and human safety. In this paper, the critical part of autonomous vessel system are the vision and sensing technology. Designing the vision part will be the most crucial task as the decision-making process made by the autonomous system need to be very accurate. Smart imaging system will be focused on to detect and recognize obstacle at 8 different distance in front of the camera system. Object detection is defined as a technical process of detection on object interest and mostly done after filtering the image using several well-known methods such as canny edge detection, Sobel edge detection, Laplacian edge detection, cartoonizer technique and colour segmentation. Edge detection is very important for the object detector to be able to increase the percentage of detection of object interest. Data of images will be convert to 2 dimensional of grayscale images to enhance the edge of two different pixels intensity.

Item Type: Final Year Project
Academic Subject : Academic Department - Electrical And Electronics - Pervasisve Systems - Microelectronics - Device Characterisation
Subject: UNSPECIFIED
Divisions: Engineering > Electrical and Electronic
Depositing User: Ahmad Suhairi Mohamed Lazim
Date Deposited: 20 Dec 2019 16:14
Last Modified: 20 Dec 2019 16:14
URI: http://utpedia.utp.edu.my/id/eprint/20130

Actions (login required)

View Item View Item

Document Downloads

More statistics for this item...