Bar Code Detection Using Omnidirectional Vision for Automated Guided Vehicle Navigation

Bar Code Detection Using Omnidirectional Vision for Automated Guided Vehicle Navigation

In this paper, a study on detectability and readability of barcodes using omnidirectional vision system for automated guided vehicle is presented. Images from omnidirectional camera are known to be distorted against the height of the object. We present an algorithm for detecting and reading barcodes...

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Main Authors: Zahari, Taha, Jessnor Arif, Mat Jizat, Ismayuzri, Ishak
Format: Conference or Workshop Item
Language:English
Published: 2012
Subjects:
TS Manufactures
TL Motor vehicles. Aeronautics. Astronautics
Online Access:http://umpir.ump.edu.my/id/eprint/2375/1/AC12769.pdf
http://umpir.ump.edu.my/id/eprint/2375/
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Institution: Universiti Malaysia Pahang
Language: English
id my.ump.umpir.2375
record_format eprints
spelling my.ump.umpir.23752018-01-22T02:35:38Z http://umpir.ump.edu.my/id/eprint/2375/ Bar Code Detection Using Omnidirectional Vision for Automated Guided Vehicle Navigation Zahari, Taha Jessnor Arif, Mat Jizat Ismayuzri, Ishak TS Manufactures TL Motor vehicles. Aeronautics. Astronautics In this paper, a study on detectability and readability of barcodes using omnidirectional vision system for automated guided vehicle is presented. Images from omnidirectional camera are known to be distorted against the height of the object. We present an algorithm for detecting and reading barcodes successfully without correcting the image distortion. Experiments were conducted both when the AGV was in motion and at rest. Three contributing factors were identified for successful barcodes detection and reading. 2012-03-26 Conference or Workshop Item PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/2375/1/AC12769.pdf Zahari, Taha and Jessnor Arif, Mat Jizat and Ismayuzri, Ishak (2012) Bar Code Detection Using Omnidirectional Vision for Automated Guided Vehicle Navigation. In: International Conference for Automatic Control and Artificial Intelligence 2012, 24-27 March 2012 , Xiamen, China. . (Unpublished)
institution Universiti Malaysia Pahang
building UMP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Pahang
content_source UMP Institutional Repository
url_provider http://umpir.ump.edu.my/
language English
topic TS Manufactures
TL Motor vehicles. Aeronautics. Astronautics
spellingShingle TS Manufactures
TL Motor vehicles. Aeronautics. Astronautics
Zahari, Taha
Jessnor Arif, Mat Jizat
Ismayuzri, Ishak
Bar Code Detection Using Omnidirectional Vision for Automated Guided Vehicle Navigation
description In this paper, a study on detectability and readability of barcodes using omnidirectional vision system for automated guided vehicle is presented. Images from omnidirectional camera are known to be distorted against the height of the object. We present an algorithm for detecting and reading barcodes successfully without correcting the image distortion. Experiments were conducted both when the AGV was in motion and at rest. Three contributing factors were identified for successful barcodes detection and reading.
format Conference or Workshop Item
author Zahari, Taha
Jessnor Arif, Mat Jizat
Ismayuzri, Ishak
author_facet Zahari, Taha
Jessnor Arif, Mat Jizat
Ismayuzri, Ishak
author_sort Zahari, Taha
title Bar Code Detection Using Omnidirectional Vision for Automated Guided Vehicle Navigation
title_short Bar Code Detection Using Omnidirectional Vision for Automated Guided Vehicle Navigation
title_full Bar Code Detection Using Omnidirectional Vision for Automated Guided Vehicle Navigation
title_fullStr Bar Code Detection Using Omnidirectional Vision for Automated Guided Vehicle Navigation
title_full_unstemmed Bar Code Detection Using Omnidirectional Vision for Automated Guided Vehicle Navigation
title_sort bar code detection using omnidirectional vision for automated guided vehicle navigation
publishDate 2012
url http://umpir.ump.edu.my/id/eprint/2375/1/AC12769.pdf
http://umpir.ump.edu.my/id/eprint/2375/
_version_ 1643664604182609920

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