An Approach of Canny Edge Detection with Virtual Hexagonal Image Structure

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dc.contributor.author He, S
dc.contributor.author Jia, W
dc.contributor.author Wu, Q
dc.contributor.editor Wen, C
dc.contributor.editor Pham, TC
dc.date.accessioned 2010-05-28T09:59:26Z
dc.date.issued 2008-01
dc.identifier.citation International Conference on Control, Automation, Robotics and Vision, 2008, pp. 879 - 882
dc.identifier.isbn 978-1-4244-2287-6
dc.identifier.other E1 en_US
dc.identifier.uri http://hdl.handle.net/10453/10771
dc.description.abstract Edge detection plays an important role in the areas of image processing, multimedia and computer vision. Gradient-based edge detection is a straightforward method to identify the edge points in the original grey-level image. It is intuitive that, in the human vision system, the edge points always appear where the gradient magnitude assumes a maximum. Hexagonal structure is an image structure alternative to traditional square image structure. The geometrical arrangement of pixels on a hexagonal structure can be described as a collection of hexagonal pixels. Because all the existing hardware for capturing image and for displaying image are produced based on square structure, an approach that uses bilinear interpolation and tri-linear interpolation is applied for conversion between square and hexagonal structures. Based on this approach, an edge detection method is proposed. This method performs Gaussian filtering to suppress image noise and computes gradients on the hexagonal structure. The pixel edge strengths on the square structure are then estimated before Canny's edge detector is applied to determine the final edge map. The experimental results show that the proposed method improves the edge detection accuracy and efficiency.
dc.publisher IEEE
dc.relation.isbasedon 10.1109/ICARCV.2008.4795633
dc.title An Approach of Canny Edge Detection with Virtual Hexagonal Image Structure
dc.type Conference Proceeding
dc.parent International Conference on Control, Automation, Robotics and Vision
dc.journal.number en_US
dc.publocation Singapore en_US
dc.publocation Singapore
dc.publocation Singapore
dc.identifier.startpage 879 en_US
dc.identifier.endpage 882 en_US
dc.cauo.name INEXT Research Strength Core en_US
dc.conference Verified OK en_US
dc.conference International Conference on Control, Automation, Robotics and Vision
dc.conference International Conference on Control, Automation, Robotics and Vision
dc.conference International Conference on Control, Automation, Robotics and Vision
dc.for 0909 Geomatic Engineering
dc.personcode 990421
dc.personcode 000748
dc.personcode 044299
dc.percentage 100 en_US
dc.classification.name Geomatic Engineering en_US
dc.classification.type FOR-08 en_US
dc.edition en_US
dc.custom en_US
dc.custom International Conference on Control, Automation, Robotics and Vision en_US
dc.date.activity 20081217 en_US
dc.date.activity 2008-12-17
dc.date.activity 2008-12-17
dc.date.activity 2008-12-17
dc.location.activity Hanoi, Vietnam en_US
dc.location.activity Hanoi, Vietnam
dc.location.activity Hanoi, Vietnam
pubs.embargo.period Not known
pubs.organisational-group /University of Technology Sydney
pubs.organisational-group /University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group /University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computing and Communications
utslib.copyright.status Closed Access
utslib.copyright.date 2015-04-15 12:17:09.805752+10
utslib.copyright.date 2015-04-15 12:17:09.805752+10
pubs.consider-herdc true
pubs.consider-herdc true
utslib.collection.history Closed (ID: 3)


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