Region Competition: Unifying Snakes, Region Growing, and Bayes/MDL for Multiband Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Normalized Cuts and Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image Segmentation by Data-Driven Markov Chain Monte Carlo
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Multiphase Level Set Framework for Image Segmentation Using the Mumford and Shah Model
International Journal of Computer Vision
Bottom-Up Hierarchical Image Segmentation Using Region Competition and the Mumford-Shah Functional
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 02
A logic framework for active contours on multi-channel images
Journal of Visual Communication and Image Representation
Solving the Chan-Vese model by a multiphase level set algorithm based on the topological derivative
SSVM'07 Proceedings of the 1st international conference on Scale space and variational methods in computer vision
IEEE Transactions on Image Processing
Image segmentation and selective smoothing by using Mumford-Shah model
IEEE Transactions on Image Processing
A binary level set model and some applications to Mumford-Shah image segmentation
IEEE Transactions on Image Processing
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Variational models have been studied for image segmentation application since the Mumford-Shah functional was introduced in the late 1980s. In this paper, we focus on multiphase segmentation with a new regularization term that yields an unsupervised segmentation model. We propose a functional that automatically chooses a favorable number of phases as it segments the image. The primary driving force of the segmentation is the intensity fitting term while a phase scale measure complements the regularization term.We propose a fast, yet simple, brute-force numerical algorithm and present experimental results showing the robustness and stability of the proposed model.