An Exact Method for Computing the Area Moments of Wavelet and Spline Curves
IEEE Transactions on Pattern Analysis and Machine Intelligence
An Active Contour Model for Segmentation Based on Cubic B-splines and Gradient Vector Flow
MICCAI '01 Proceedings of the 4th International Conference on Medical Image Computing and Computer-Assisted Intervention
Frequency Domain Formulation of Active Parametric Deformable Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
G-wire: A livewire segmentation algorithm based on a generalized graph formulation
Pattern Recognition Letters
Segmentation of a Vector Field: Dominant Parameter and Shape Optimization
Journal of Mathematical Imaging and Vision
B-Spline curve smoothing under position constraints for line generalisation
GIS '06 Proceedings of the 14th annual ACM international symposium on Advances in geographic information systems
Boundary vector field for parametric active contours
Pattern Recognition
Journal of Mathematical Imaging and Vision
Locally regularized smoothing B-snake
EURASIP Journal on Applied Signal Processing
A novel algorithm of surface eliminating in undersurface optoacoustic imaging
EURASIP Journal on Applied Signal Processing
Cartographic generalisation of lines based on a B-spline snake model
International Journal of Geographical Information Science
Robust B-spline Snakes For Ultrasound Image Segmentation
Journal of Signal Processing Systems
Force field analysis snake: an improved parametric active contour model
Pattern Recognition Letters
Sub-pixel edge fitting using B-spline
MIRAGE'07 Proceedings of the 3rd international conference on Computer vision/computer graphics collaboration techniques
Reconstruction of 3D curves for quality control
SCIA'07 Proceedings of the 15th Scandinavian conference on Image analysis
Variational guidewire tracking using phase congruency
MICCAI'07 Proceedings of the 10th international conference on Medical image computing and computer-assisted intervention
Energy-based reconstruction of 3D curves for quality control
EMMCVPR'07 Proceedings of the 6th international conference on Energy minimization methods in computer vision and pattern recognition
Parametric active contour model by using the honey bee mating optimization
Expert Systems with Applications: An International Journal
Information Sciences: an International Journal
Polar snakes: a fast and robust parametric active contour model
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
ROBIO'09 Proceedings of the 2009 international conference on Robotics and biomimetics
Image contour extraction based on ant colony algorithm and B-snake
ICIC'10 Proceedings of the 6th international conference on Advanced intelligent computing theories and applications: intelligent computing
A new adaptive B-spline VFC snake for object contour extraction
ICCCI'10 Proceedings of the Second international conference on Computational collective intelligence: technologies and applications - Volume Part III
3D cylindrical B-spline segmentation of carotid arteries from MRI images
ISBMS'06 Proceedings of the Third international conference on Biomedical Simulation
Visualization of tooth for 3-d simulation
AsiaSim'04 Proceedings of the Third Asian simulation conference on Systems Modeling and Simulation: theory and applications
Original Articles: Nonparametric edge detection in speckled imagery
Mathematics and Computers in Simulation
Comparative study of segmentation methods for tree leaves extraction
Proceedings of the International Workshop on Video and Image Ground Truth in Computer Vision Applications
Boundary reconstruction in binary images using splines
Pattern Recognition
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We present a novel formulation for B-spline snakes that can be used as a tool for fast and intuitive contour outlining. We start with a theoretical argument in favor of splines in the traditional formulation by showing that the optimal, curvature-constrained snake is a cubic spline, irrespective of the form of the external energy field. Unfortunately, such regularized snakes suffer from slow convergence speed because of a large number of control points, as well as from difficulties in determining the weight factors associated to the internal energies of the curve. We therefore propose an alternative formulation in which the intrinsic scale of the spline model is adjusted a priori; this leads to a reduction of the number of parameters to be optimized and eliminates the need for internal energies (i.e., the regularization term). In other words, we are now controlling the elasticity of the spline implicitly and rather intuitively by varying the spacing between the spline knots. The theory is embedded into a multiresolution formulation demonstrating improved stability in noisy image environments. Validation results are presented, comparing the traditional snake using internal energies and the proposed approach without internal energies, showing the similar performance of the latter. Several biomedical examples of applications are included to illustrate the versatility of the method