Image Transformation on Hexagonal Structure Based on Conversion between 1D and 2D Coordinates

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dc.contributor.author Ye, Y
dc.contributor.author He, S
dc.contributor.author Li, J
dc.contributor.author Jia, W
dc.contributor.author Wu, Q
dc.contributor.editor Wen, P
dc.contributor.editor Li, Y
dc.contributor.editor Polkowski, L
dc.contributor.editor Yao, Y
dc.contributor.editor Tsumoto, S
dc.contributor.editor Wang, G
dc.date.accessioned 2010-05-28T09:38:07Z
dc.date.issued 2009-01
dc.identifier.citation Rough Sets and Knowledge Technology, 2009, 1, pp. 571 - 578
dc.identifier.isbn 978-3-642-02961-5
dc.identifier.other B1 en_US
dc.identifier.uri http://hdl.handle.net/10453/7838
dc.description.abstract Spiral Architecture, a hexagonal image structure is a novel and powerful approach to machine vision system. The pixels on Spiral architecture are geometrically arranged using a 1D (Spiral) addressing scheme in an ascending order along a spiral-like curve. Spiral addition and Spiral multiplication are defined based on the Spiral addresses on Spiral Architecture. These two fundamental operations result in fast and easy translation, rotation and separation on images, and hence play very important roles for image processing on Spiral Architecture. Moreover, 2D coordinates according to rows and columns defined on Spiral Structure provide a good mapping to the ordinary 2D coordinates defined on the common square image structure. Therefore, how to convert the 1D Spiral addresses from and to the 2D coordinates on Spiral Architecture has become very important to apply the theory developed on a hexagonal image structure for image processing (e.g., rotation). In this paper, we perform a fast way to correctly locate any hexagonal pixel when its Spiral address is known, and compute the Spiral address of any hexagonal pixel when its location is known. As an illustration of the use of conversions, we demonstrate the accurate image translation and rotation using experimental results.
dc.publisher Springer
dc.relation.hasversion Accepted manuscript version
dc.relation.isbasedon 10.1007/978-3-642-02962-2
dc.title Image Transformation on Hexagonal Structure Based on Conversion between 1D and 2D Coordinates
dc.type Chapter
dc.parent Rough Sets and Knowledge Technology
dc.journal.number en_US
dc.publocation Berlin, Germany en_US
dc.publocation Berlin, Germany
dc.publocation Berlin, Germany
dc.identifier.startpage 571 en_US
dc.identifier.endpage 578 en_US
dc.cauo.name FEIT.Faculty of Engineering & Information Technology en_US
dc.conference Verified OK en_US
dc.for 080106 Image Processing
dc.for 080104 Computer Vision
dc.for 080109 Pattern Recognition and Data Mining
dc.personcode 990421
dc.personcode 000748
dc.personcode 044299
dc.percentage 40 en_US
dc.classification.name Image Processing en_US
dc.classification.type FOR-08 en_US
dc.edition 1 en_US
dc.edition 1
dc.edition 1
dc.custom en_US
dc.date.activity en_US
dc.location.activity en_US
dc.description.keywords Hexagonal structure - Spiral Architecture - image transformation
dc.description.keywords Hexagonal structure - Spiral Architecture - image transformation
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 Open Access
utslib.copyright.date 2015-04-15 12:23:47.074767+10
utslib.copyright.date 2015-04-15 12:23:47.074767+10
pubs.consider-herdc true
pubs.consider-herdc true
utslib.collection.history General (ID: 2)


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