Android smart phone based participatory sensing

In recent years, there is an increasing market demand for mobile navigation application. However, current navigation application only provides a driving path which drivers may not know which lane to stay in to make a turn. One of the improvements is to provide lane information to drivers through rea...

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Main Author: Goh, Yee Ting
Other Authors: Li Mo
Format: Final Year Project
Language:English
Published: 2015
Subjects:
Online Access:http://hdl.handle.net/10356/62803
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-628032023-03-03T20:49:44Z Android smart phone based participatory sensing Goh, Yee Ting Li Mo School of Computer Engineering Parallel and Distributed Computing Centre DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision In recent years, there is an increasing market demand for mobile navigation application. However, current navigation application only provides a driving path which drivers may not know which lane to stay in to make a turn. One of the improvements is to provide lane information to drivers through real-time lane detection with the use of an Android mobile phone. This project proposes a robust and real-time lane detection that is able to detect all the lanes and to identify the current car position. Firstly, the algorithm of lane detection is based on transforming a front facing image to a bird-eye view image in order to make lane markers to appear vertical with almost equal width. Secondly, Canny edge detector is used to obtain edges of an image and lines are detected by Hough line transform. Next, grouping of lines is used to obtain a robust line from a group of nearby lines where these lines are used to identify the lane markers on the road and to identify the current car position. The experimental result shows that all the lanes are detected and is able to keep track of current car position when there is a lane change. In addition, the proposed algorithm is able to identify the missing lane markers and dynamically insert a lane marker at the correct position. Bachelor of Engineering (Computer Science) 2015-04-29T04:30:59Z 2015-04-29T04:30:59Z 2015 2015 Final Year Project (FYP) http://hdl.handle.net/10356/62803 en Nanyang Technological University 52 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision
spellingShingle DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision
Goh, Yee Ting
Android smart phone based participatory sensing
description In recent years, there is an increasing market demand for mobile navigation application. However, current navigation application only provides a driving path which drivers may not know which lane to stay in to make a turn. One of the improvements is to provide lane information to drivers through real-time lane detection with the use of an Android mobile phone. This project proposes a robust and real-time lane detection that is able to detect all the lanes and to identify the current car position. Firstly, the algorithm of lane detection is based on transforming a front facing image to a bird-eye view image in order to make lane markers to appear vertical with almost equal width. Secondly, Canny edge detector is used to obtain edges of an image and lines are detected by Hough line transform. Next, grouping of lines is used to obtain a robust line from a group of nearby lines where these lines are used to identify the lane markers on the road and to identify the current car position. The experimental result shows that all the lanes are detected and is able to keep track of current car position when there is a lane change. In addition, the proposed algorithm is able to identify the missing lane markers and dynamically insert a lane marker at the correct position.
author2 Li Mo
author_facet Li Mo
Goh, Yee Ting
format Final Year Project
author Goh, Yee Ting
author_sort Goh, Yee Ting
title Android smart phone based participatory sensing
title_short Android smart phone based participatory sensing
title_full Android smart phone based participatory sensing
title_fullStr Android smart phone based participatory sensing
title_full_unstemmed Android smart phone based participatory sensing
title_sort android smart phone based participatory sensing
publishDate 2015
url http://hdl.handle.net/10356/62803
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