- Title
- Performance comparisons of contour-based corner detectors
- Creator
- Awrangjeb, Mohammad; Lu, Guojun; Fraser, Clive
- Date
- 2012
- Type
- Text; Journal article
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/74256
- Identifier
- vital:7231
- Identifier
- ISSN:1057-7149
- Abstract
- Abstract— Corner detectors have many applications in computer vision and image identification and retrieval. Contour-based corner detectors directly or indirectly estimate a significance measure (e.g., curvature) on the points of a planar curve, and select the curvature extrema points as corners. While an extensive number of contour-based corner detectors have been proposed over the last four decades, there is no comparative study of recently proposed detectors. This paper is an attempt to fill this gap. The general framework of contour-based corner detection is presented, and two major issues – curve smoothing and curvature estimation, which have major impacts on the corner detection performance, are discussed. A number of promising detectors are compared using both automatic and manual evaluation systems on two large datasets. It is observed that while the detectors using indirect curvature estimation techniques are more robust, the detectors using direct curvature estimation techniques are faster.
- Relation
- IEEE Transactions on Image Processing Vol. 21, no. 9 (2012), p. 4167-4179
- Rights
- Copyright IEEE
- Rights
- This metadata is freely available under a CCO license
- Subject
- 0801 Artificial Intelligence and Image Processing; 0906 Electrical and Electronic Engineering; 1702 Cognitive Science; Accuracy; Chord-to-point distance; Accumulation (CPDA); Corner detection; Fast-CPDA; Performance study; Robustness
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