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
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 Image Processing
IEEE Transactions on Image Processing
RAGS: region-aided geometric snake
IEEE Transactions on Image Processing
Region-Based Active Contours with Exponential Family Observations
Journal of Mathematical Imaging and Vision
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Object extraction or image segmentation is a basic problem in image analysis and computer vision. It has been dealt with in various forms. Variational method is an emerging framework to tackle such problems where the aim is to create an image partition that follows the data while at the same time preserving certain regularity. In this paper, we propose a new energy functional which is based on the region information of an image. The region-based force makes our variational flow robust to noise and provides a global segmentation criterion. Furthermore, our method is implemented using level set theory, which makes it easy to deal with topological changes. Finally, in order to simultaneously segment a number of different objects in an image, a hierarchical method is presented.