Name
Abstract | ||
|---|---|---|
Parametric active contours are efficient tools for boundary detection. However, existing external-energy-inspired methods have difficulties when detecting high curvature, noisy or low contrasted contours and they often suffer from initialization sensitivity. To address these issues, this paper introduces Harris-based Vector Field Convolution (HVFC), operating with the modified characteristic function of Harris corner detector used in the feature map of the external force component. Initial contour is calculated as the convex hull of the most salient points of the map. Experimental results show that HVFC outperforms other state-of-the-art methods, when tested on high curvature, noisy or low-contrasted contours. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/ICIP.2011.6116142 | ICIP |
Keywords | Field | DocType |
convolution,edge detection,feature extraction,vectors,HVFC,boundary detection,convex hull,external force component,feature map,force field,high curvature contour,initialization sensitivity,low contrasted contour,modified Harris corner detector characteristic function,noisy contours,parametric active contour,vector field convolution method,Boundary analysis,Harris characteristic function,vector field convolution | Curvature,Corner detection,Pattern recognition,Convolution,Edge detection,Computer science,Convex hull,Feature extraction,Parametric statistics,Artificial intelligence,Initialization | Conference |
ISSN | Citations | PageRank |
1522-4880 | 5 | 0.43 |
References | Authors | |
8 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Andrea Kovács | 1 | 37 | 3.56 |
| Tamás Szirányi | 2 | 152 | 26.92 |