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Comparing Hexagonal Image Resampling Techniques with Respect to Feature Extraction

Biomedical Sciences Research Institute Computer Science Research Institute Environmental Sciences Research Institute Nanotechnology & Advanced Materials Research Institute

Gardiner, Bryan, Coleman, SA and Scotney, BW (2011) Comparing Hexagonal Image Resampling Techniques with Respect to Feature Extraction. In: 14th International Machine Vision and Image Processing Conference, University of Limerick, Ireland. Cambridge Scholars. 13 pp. [Conference contribution]

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Abstract

The hexagonal structure is considered to be preferable to the standard rectangular structure typically used for images in terms of the improved accuracy and efficiency that can be achieved for a number of image processing tasks. However, due to the lack of commercially available hexagonal image sensors, hexagonally structured images are generated by resampling from standard rectangular images and hence many resampling techniques exist for this purpose. Here we consider four such resampling techniques and apply recently developed scalable operators to them for the purpose of feature extraction. Each hexagonally structure image is evaluated with respect to feature extraction performance and we provide conclusions on the most accurate resampling technique currently available.

Item Type:Conference contribution (Paper)
Faculties and Schools:Faculty of Computing & Engineering
Faculty of Computing & Engineering > School of Computing and Information Engineering
Faculty of Computing & Engineering > School of Computing and Intelligent Systems
Research Institutes and Groups:Computer Science Research Institute
Computer Science Research Institute > Information and Communication Engineering
Computer Science Research Institute > Intelligent Systems Research Centre
ID Code:20174
Deposited By:Dr Bryan Gardiner
Deposited On:07 Oct 2011 13:51
Last Modified:07 Oct 2011 13:51

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