The quickhull algorithm for convex hulls
ACM Transactions on Mathematical Software (TOMS)
Evaluation of Interest Point Detectors
International Journal of Computer Vision - Special issue on a special section on visual surveillance
Flux Maximizing Geometric Flows
IEEE Transactions on Pattern Analysis and Machine Intelligence
Regularized Laplacian Zero Crossings as Optimal Edge Integrators
International Journal of Computer Vision
Gradient Vector Flow: A New External Force for Snakes
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
A New Active Convex Hull Model for Image Regions
Journal of Mathematical Imaging and Vision
NGVF: An improved external force field for active contour model
Pattern Recognition Letters
Focus Area Extraction by Blind Deconvolution for Defining Regions of Interest
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fast Global Minimization of the Active Contour/Snake Model
Journal of Mathematical Imaging and Vision
Quasi-automatic initialization for parametric active contours
Pattern Recognition Letters
Gradient vector flow active contours with prior directional information
Pattern Recognition Letters
Decoupled Active Contour (DAC) for Boundary Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Harris 3D: a robust extension of the Harris operator for interest point detection on 3D meshes
The Visual Computer: International Journal of Computer Graphics - Special Issue on 3DOR 2010
IEEE Transactions on Image Processing
A downstream algorithm based on extended gradient vector flow field for object segmentation
IEEE Transactions on Image Processing
Dynamic directional gradient vector flow for snakes
IEEE Transactions on Image Processing
Global Regularizing Flows With Topology Preservation for Active Contours and Polygons
IEEE Transactions on Image Processing
Active Contour External Force Using Vector Field Convolution for Image Segmentation
IEEE Transactions on Image Processing
An active contour computer algorithm for the classification of cucumbers
Computers and Electronics in Agriculture
Adaptive diffusion flow active contours for image segmentation
Computer Vision and Image Understanding
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Deformable active contour (snake) models are efficient tools for object boundary detection. Existing alterations of the traditional gradient vector flow (GVF) model have reduced sensitivity to noise, parameters and initial location, but high curvatures and noisy, weakly contrasted boundaries cause difficulties for them. This paper introduces two Harris based parametric snake models, Harris based gradient vector flow (HGVF) and Harris based vector field convolution (HVFC), which use the curvature-sensitive Harris matrix to achieve a balanced, twin-functionality (corner and edge) feature map. To avoid initial location sensitivity, starting contour is defined as the convex hull of the most attractive points of the map. In the experimental part we compared our methods to the traditional external energy-inspired state-of-the-art GVF and VFC; the recently published parametric decoupled active contour (DAC) and the non-parametric Chan-Vese (ACWE) techniques. Results show that our methods outperform the classical approaches, when tested on images with high curvature, noisy boundaries.