Visual reconstruction
Fronts propagating with curvature-dependent speed: algorithms based on Hamilton-Jacobi formulations
Journal of Computational Physics
Hierarchy in Picture Segmentation: A Stepwise Optimization Approach
IEEE Transactions on Pattern Analysis and Machine Intelligence
Integrating Region Growing and Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
On active contour models and balloons
CVGIP: Image Understanding
Watersheds in Digital Spaces: An Efficient Algorithm Based on Immersion Simulations
IEEE Transactions on Pattern Analysis and Machine Intelligence
A multiscale algorithm for image segmentation by variational method
SIAM Journal on Numerical Analysis
Variational methods in image segmentation
Variational methods in image segmentation
Region Competition: Unifying Snakes, Region Growing, and Bayes/MDL for Multiband Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
International Journal of Computer Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Study of a Convex Variational Diffusion Approach for Image Segmentation and Feature Extraction
Journal of Mathematical Imaging and Vision
A hierarchical Markov modeling approach for the segmentation and tracking of deformable shapes
Graphical Models and Image Processing
A Markov Pixon Information Approach for Low-Level Image Description
IEEE Transactions on Pattern Analysis and Machine Intelligence
Statistical Region Snake-Based Segmentation Adapted to Different Physical Noise Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
Topographic Maps and Local Contrast Changes in Natural Images
International Journal of Computer Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Cooperative Robust Estimation Using Layers of Support
IEEE Transactions on Pattern Analysis and Machine Intelligence
Segmentation of Bone in Clinical Knee MRI Using Texture-Based Geodesic Active Contours
MICCAI '98 Proceedings of the First International Conference on Medical Image Computing and Computer-Assisted Intervention
Globally Optimal Regions and Boundaries
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
A Statistical Approach to Snakes for Bimodal and Trimodal Imagery
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Fast computation of a contrast-invariant image representation
IEEE Transactions on Image Processing
Scale space classification using area morphology
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
Flat zones filtering, connected operators, and filters by reconstruction
IEEE Transactions on Image Processing
A color topographic map based on the dichromatic reflectance model
Journal on Image and Video Processing - Color in Image and Video Processing
Novel classification and segmentation techniques with application to remotely sensed images
Transactions on rough sets VII
Body color sets: A compact and reliable representation of images
Journal of Visual Communication and Image Representation
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We propose a variational framework for determining global minimizers of rough energy functionals used in image segmentation. Segmentation is achieved by minimizing an energy model, which is comprised of two parts: the first part is the interaction between the observed data and the model, the second is a regularity term. The optimal boundaries are the curves that globally minimize the energy functional. Our motivation comes from the observation that energy functionals are traditionally complex, for which it is usually difficult to precise global minimizers corresponding to “best” segmentations. Therefore, we focus on basic energy models, which global minimizers can be characterized. None of the proposed segmentation models captures all the important scene variables but may be useful to get an insight into objects, surfaces or parts of objects in the scene. In this paper, we prove that the set of curves that minimizes the cost functionals is a subset of level lines, i.e. the boundaries of level sets of the image. For the completeness of the paper, we present a fast algorithm for computing partitions with connected components. It leads to a sound initialization-free algorithm without any hidden parameter to be tuned. We illustrate the performance of our algorithm with several examples on both 2D biomedical and aerial images, and synthetic images.