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Adaptive Application of Feature Detection Operators Based on Image Variance

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

Coleman, SA, Scotney, BW and Herron, MG (2004) Adaptive Application of Feature Detection Operators Based on Image Variance. Pattern Recognition, 37 (12). pp. 2403-2406. [Journal article]

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URL: http://dx.doi.org/10.1016/j.patcog.2004.05.006

DOI: 10.1016/j.patcog.2004.05.006

Abstract

It is well known that the strength of a feature in an image may depend on the scale at which the appropriate detection operator is applied. It is also the case that many features in images exist significantly over a limited range of scales, and, of particular interest here, that the most salient scale may vary spatially over the feature. Hence, when designing feature detection operators, it is necessary to consider the requirements for both the systematic development and adaptive application of such operators over scale- and image-domains. We present an overview to the design of scalable derivative edge detectors, based on the finite element method, that addresses the issues of method and scale-adaptability. The finite element approach allows us to formulate scalable image derivative operators that can be implemented using a combination of piecewise-polynomial and Gaussian basis functions. The general adaptive technique may be applied to a range of operators. Here we evaluate the approach using image gradient operators, and we present comparative qualitative and quantitative results for both first and second order derivative methods.

Item Type:Journal article
Keywords:Adaptive filtering; Feature detection; Scale; Image variance
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
Faculty of Computing & Engineering > School of Computing and Mathematics
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:6810
Deposited By:Professor Bryan Scotney
Deposited On:20 Jan 2010 15:49
Last Modified:15 Jun 2011 11:07

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