View source for Publications:Row-detection on an agricultural field using omnidirectional camera

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{{PublicationSetupTemplate|Author=Stefan Ericson, Björn Åstrand
|PID=408052
|Name=Ericson, Stefan (School of Technology and Society, University of Skövde, Skövde);Åstrand, Björn (bjorn) (Högskolan i Halmstad (2804), Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE) (3905), Halmstad Embedded and Intelligent Systems Research (EIS) (3938))
|Title=Row-detection on an agricultural field using omnidirectional camera
|PublicationType=Conference Paper
|ContentType=Refereegranskat
|Language=eng
|Journal=
|JournalISSN=
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|HostPublication=2010 IEEE/RSJ international conference on intelligent robots and systems
|Conference=The 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems October 18-22, 2010, Taipei, Taiwan
|StartPage=4982
|EndPage=4987
|Year=2010
|Edition=
|Pages=
|City=Piscataway, N.J.
|Publisher=IEEE Press
|Series=IEEE International Conference on Intelligent Robots and Systems
|SeriesISSN=2153-0858
|ISBN=9781424466740
|Urls=
|ISRN=
|DOI=http://dx.doi.org/10.1109/IROS.2010.5650964
|ISI=000287672004089
|PMID=
|ScopusId=2-s2.0-78651477189
|NBN=urn:nbn:se:hh:diva-14701
|LocalId=
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|Keywords=Hough transform method;agricultural field;calibration data;catadioptric len;edge based method;omnidirectional camera;real field image;row detection;synthetic image;using fisheye lens;vanishing point;Hough transforms;agricultural machinery;calibration;edge detection;mobile robots;photographic lenses
|Categories=Teknik och teknologier (2);Robotteknik och automation (20201)
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|Abstract=<p>This paper describes a method of detecting parallel rows on an agricultural field using an omnidirectional camera. The method works both on cameras with a fisheye lens and cameras with a catadioptric lens. A combination of an edge based method and a Hough transform method is suggested to find the rows. The vanishing point of several parallel rows is estimated using a second Hough transform. The method is evaluated on synthetic images generated with calibration data from real lenses. Scenes with several rows are produced, where each plant is positioned with a specified error. Experiments are performed on these synthetic images and on real field images. The result shows that good accuracy is obtained on the vanishing point once it is detected correctly. Further it shows that the edge based method works best when the rows consists of solid lines, and the Hough method works best when the rows consists of individual plants. The experiments also show that the combined method provides better detection than using the methods separately.</p>
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|CreatedDate=2011-04-02
|PublicationDate=2011-04-02
|LastUpdated=2013-02-08
|diva=http://hh.diva-portal.org/smash/record.jsf?searchId=1&pid=diva2:408052}}
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