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Robust Feature Matching Using The FESID Detector

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

Kerr, D, Coleman, SA and Scotney, BW (2011) Robust Feature Matching Using The FESID Detector. In: International Machine Vision and Image Processing Conference (IMVIP 2010), Limerick, Ireland. Cambridge Scholars Publishing, 12 Back Chapman Street, Newcastle upon Tyne, NE6 2XX, UK. 12 pp. [Conference contribution]

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URL: http://www.c-s-p.org/flyers/14th-International-Machine-Vision-and-Image-Processing-Conference--IMVIP-20101-4438-2962-5.htm

Abstract

Recently, interest point detectors and descriptors have become prominent in the field of computer vision and are typically used to determine correspondences between two images of the same scene. The finite element scale invariant detector (FESID) is based on a similar multi-scale approach to that used in the SURF detector. However, FESID detects point features rather than blob features, and by combining the derivative and smoothing operations into a single operator efficient performance is achieved. We illustrate the performance of the FESID algorithm with respect to both robustness and correct region matching.

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:20481
Deposited By:Dr Dermot Kerr
Deposited On:15 Nov 2011 11:08
Last Modified:15 Nov 2011 11:08

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