FESID: Finite Element Scale Invariant Detector

Authors:
Dermot Kerr;Sonya Coleman;Bryan Scotney
Affiliations:
School of Computing and Intelligent Systems, University of Ulster, Magee, Northern Ireland BT48 7JL;School of Computing and Intelligent Systems, University of Ulster, Magee, Northern Ireland BT48 7JL;School of Computing and Information Engineering, University of Ulster, Coleraine, Northern Ireland BT52 1SA
Venue:
ICIAP '09 Proceedings of the 15th International Conference on Image Analysis and Processing
Year:
2009

Citing 9
Cited 1

Comparing and Evaluating Interest Points

ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Scale & Affine Invariant Interest Point Detectors

International Journal of Computer Vision
Distinctive Image Features from Scale-Invariant Keypoints

International Journal of Computer Vision
A Comparison of Affine Region Detectors

International Journal of Computer Vision
Improving angular error via systematically designed near-circular Gaussian-based feature extraction operators

Pattern Recognition
Integrated Edge and Corner Detection

ICIAP '07 Proceedings of the 14th International Conference on Image Analysis and Processing
Near-Circular Corner and Edge Detection Operators

IMVIP '07 Proceedings of the International Machine Vision and Image Processing Conference
Speeded-Up Robust Features (SURF)

Computer Vision and Image Understanding
SURF: speeded up robust features

ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part I

A finite element blob detector for robust features

ICIAP'11 Proceedings of the 16th international conference on Image analysis and processing: Part I

Quantified Score

Hi-index	0.00

Visualization

Abstract

Recently, finite element based methods have been used to develop gradient operators for edge detection that have improved angular accuracy over standard techniques. A more prominent issue in the field of image processing has become the use of interest point detectors and to this end we expand upon this research developing a finite element scale invariant interest point detector that is based on the same multi-scale approach used in the SURF detector. The operator differs in that the autocorrelation matrix is used to select the interest point location and the derivative and smoothing operations are combined into one operator developed through the use of the finite element framework.