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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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 |
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DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision Goh, Yee Ting Android smart phone based participatory sensing |
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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. |
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Li Mo |
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Li Mo Goh, Yee Ting |
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Final Year Project |
author |
Goh, Yee Ting |
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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 |
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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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1759854893702578176 |