Performance assessment of feature detection algorithms: a methodology and case study on corner detectors

Peter I Rockett

doi:10.1109/TIP.2003.818041

Performance assessment of feature detection algorithms: a methodology and case study on corner detectors

IEEE Trans Image Process. 2003;12(12):1668-76. doi: 10.1109/TIP.2003.818041.

Author

Peter I Rockett¹

Affiliation

¹ Department of Electronic and Electrical Engineering, University of Sheffield, Sheffield S1 3JD, UK. p.rockett@ shef.ac.uk

PMID: 18244720
DOI: 10.1109/TIP.2003.818041

Abstract

In this paper, we describe a generic methodology for evaluating the labeling performance of feature detectors. We describe a method for generating a test set and apply the methodology to the performance assessment of three well-known corner detectors: the Kitchen-Rosenfeld, Paler et al., and Harris-Stephens corner detectors. The labeling deficiencies of each of these detectors is related to their discrimination ability between corners and various of the features which comprise the class of noncorners.