Region Competition: Unifying Snakes, Region Growing, and Bayes/MDL for Multiband Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Level Set Model for Image Classification
International Journal of Computer Vision
A Multiphase Level Set Framework for Image Segmentation Using the Mumford and Shah Model
International Journal of Computer Vision
A Variational Framework for Active and Adaptative Segmentation of Vector Valued Images
MOTION '02 Proceedings of the Workshop on Motion and Video Computing
Unsupervised Non-parametric Region Segmentation Using Level Sets
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
The Amsterdam Library of Object Images
International Journal of Computer Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
International Journal of Computer Vision
Level Set Segmentation With Multiple Regions
IEEE Transactions on Image Processing
Unsupervised Variational Image Segmentation/Classification Using a Weibull Observation Model
IEEE Transactions on Image Processing
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In the scope of level set image segmentation, the number of regions is fixed beforehand. This number occurs as a constant in the objective functional and its optimization. In this study, we propose a region merging prior which optimizes the objective functional implicitly with respect to the number of regions. A statistical interpretation of the functional and learning over a set of relevant images and segmentation examples allow setting the weight of this prior to obtain the correct number of regions. This method is investigated and validated with color images and motion maps.