Road sign recognition for assisting drivers

For a highly reliable autonomous vehicle, it must be able to detect traffic signs and obey the traffic rules. In this paper, color segmentation is applied in YCbCr color space and shape detection is processed through blob analysis method. By calculating the circularity and area ratio with bounding b...

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Main Author: Poon, Wai Chung
Other Authors: Ma Kai Kuang
Format: Final Year Project
Language:English
Published: 2016
Subjects:
Online Access:http://hdl.handle.net/10356/67956
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-679562023-07-07T15:42:49Z Road sign recognition for assisting drivers Poon, Wai Chung Ma Kai Kuang School of Electrical and Electronic Engineering DRNTU::Engineering For a highly reliable autonomous vehicle, it must be able to detect traffic signs and obey the traffic rules. In this paper, color segmentation is applied in YCbCr color space and shape detection is processed through blob analysis method. By calculating the circularity and area ratio with bounding box, the shapes in binary images can be classified accurately. In the recognition stage, SURF algorithm is performed on both the training sets and sample images to extract the features points of the traffic signs for matching based on K-NN classifier. Bachelor of Engineering 2016-05-23T08:24:17Z 2016-05-23T08:24:17Z 2016 Final Year Project (FYP) http://hdl.handle.net/10356/67956 en Nanyang Technological University 43 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
spellingShingle DRNTU::Engineering
Poon, Wai Chung
Road sign recognition for assisting drivers
description For a highly reliable autonomous vehicle, it must be able to detect traffic signs and obey the traffic rules. In this paper, color segmentation is applied in YCbCr color space and shape detection is processed through blob analysis method. By calculating the circularity and area ratio with bounding box, the shapes in binary images can be classified accurately. In the recognition stage, SURF algorithm is performed on both the training sets and sample images to extract the features points of the traffic signs for matching based on K-NN classifier.
author2 Ma Kai Kuang
author_facet Ma Kai Kuang
Poon, Wai Chung
format Final Year Project
author Poon, Wai Chung
author_sort Poon, Wai Chung
title Road sign recognition for assisting drivers
title_short Road sign recognition for assisting drivers
title_full Road sign recognition for assisting drivers
title_fullStr Road sign recognition for assisting drivers
title_full_unstemmed Road sign recognition for assisting drivers
title_sort road sign recognition for assisting drivers
publishDate 2016
url http://hdl.handle.net/10356/67956
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