Ulster University Logo

Ulster Institutional Repository

An Empirical Performance Evaluation Technique for Discrete Second Derivative Edge Detectors

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

Coleman, SA, Scotney, BW and Herron, MG (2003) An Empirical Performance Evaluation Technique for Discrete Second Derivative Edge Detectors. In: 12th International Conference on Image Analysis and Processing (ICIAP 2003), Mantova, Italy. IEEE Computer Society. 6 pp. [Conference contribution]

Full text not available from this repository.

DOI: 10.1109/ICIAP.2003.1234115

Abstract

The problem of edge evaluation in relation to image gradient-based edge detectors has been widely studied, and there exist a range of edge evaluation techniques that are appropriate to such edge detectors. Although discrete second derivative operators often form the basis of edge detection methods, whereby zero-crossings are used to locate edge pixels, rather less attention has been paid to the development of edge evaluation techniques that are directly appropriate to zero-crossing methods. We propose a new evaluation technique that performs edge sensitivity analysis with respect to angular orientation and displacement errors for edges located by such discrete second derivative operators. The technique applies a finite element interpolation to the output values of the second derivative operator. Hence the method is used to directly evaluate edges located by a second derivative operator without the need to use a supplementary first derivative operator for gradient approximation.

Item Type:Conference contribution (Paper)
Keywords:second derivative edge detectors, performance evaluation, zero-crossings, edge sensitivity analysis
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:6802
Deposited By:Professor Bryan Scotney
Deposited On:23 May 2011 15:39
Last Modified:23 May 2011 15:39

Repository Staff Only: item control page