Visual reconstruction
Fronts propagating with curvature-dependent speed: algorithms based on Hamilton-Jacobi formulations
Journal of Computational Physics
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
Topographic Maps and Local Contrast Changes in Natural Images
International Journal of Computer Vision
Connected filtering and segmentation using component trees
Computer Vision and Image Understanding
Level Lines as Global Minimizers of Energy Functionals in Image Segmentation
ECCV '00 Proceedings of the 6th European Conference on Computer Vision-Part II
Coupled Geodesic Active Regions for Image Segmentation: A Level Set Approach
ECCV '00 Proceedings of the 6th European Conference on Computer Vision-Part II
Scales in Natural Images and a Consequence on their Bounded Variation Norm
SCALE-SPACE '99 Proceedings of the Second International Conference on Scale-Space Theories in Computer Vision
An Active Contour Model without Edges
SCALE-SPACE '99 Proceedings of the Second International Conference on Scale-Space Theories in Computer Vision
A Statistical Approach to Snakes for Bimodal and Trimodal Imagery
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Flat zones filtering, connected operators, and filters by reconstruction
IEEE Transactions on Image Processing
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Bayesian statistical theory is a convenient way of taking a priori information into consideration when inference is made from images. In Bayesian image detection, the a priori distribution should capture the knowledge about objects. Taking inspiration from [1], we design a prior density that penalizes the area of homogeneous parts in images. The detection problem is further formulated as the estimation of the set of curves that maximizes the posterior distribution. In this paper, we explore a posterior distribution model for which its maximal mode is given by a subset of level curves, that is the boundaries of image level sets. For the completeness of the paper, we present a stepwise greedy algorithm for computing partitions with connected components.