A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Statistical Inference for Spatial Processes
Statistical Inference for Spatial Processes
Boundary Detection by Constrained Optimization
IEEE Transactions on Pattern Analysis and Machine Intelligence
On active contour models and balloons
CVGIP: Image Understanding
SIAM Journal on Applied Mathematics
Object Matching Using Deformable Templates
IEEE Transactions on Pattern Analysis and Machine Intelligence
Averaging of Random Sets Based on Their Distance Functions
Journal of Mathematical Imaging and Vision
Deformable template models: a review
Signal Processing - Special issue on deformable models and techniques for image and signal processing
Efficient deformable template detection and localization without user initialization
Computer Vision and Image Understanding
Active Contours: The Application of Techniques from Graphics,Vision,Control Theory and Statistics to Visual Tracking of Shapes in Motion
Digital Image Processing
Geometrically Deformable Templates for Shape-Based Segmentation and Tracking in Cardiac MR Images
EMMCVPR '97 Proceedings of the First International Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition
A Novel Approach for Breast Skin-Line Estimation in Mammograms
CBMS '05 Proceedings of the 18th IEEE Symposium on Computer-Based Medical Systems
Computing the Fréchet distance between piecewise smooth curves
Computational Geometry: Theory and Applications
Expectations of Random Sets and Their Boundaries Using Oriented Distance Functions
Journal of Mathematical Imaging and Vision
2D and 3D shape based segmentation using deformable models
MICCAI'05 Proceedings of the 8th international conference on Medical image computing and computer-assisted intervention - Volume Part II
A multistage, optimal active contour model
IEEE Transactions on Image Processing
Snakes, shapes, and gradient vector flow
IEEE Transactions on Image Processing
B-spline snakes: a flexible tool for parametric contour detection
IEEE Transactions on Image Processing
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In image analysis, it is often required to reconstruct the boundary of an object in a noisy image. This paper presents a new method, which relies on flexibility and computational simplicity of B-spline curves, to reconstruct a smooth connected boundary in a noisy binary image. Boundary inference is based on oriented distance functions yielding the estimator which is interpreted as a posterior expected boundary of the underlying random set. The performance of the method and its dependence on the image quality and model specification are studied on simulated data. The method is applied to reconstruct the skin-air boundary in digitised analogue mammogram images.