Markov random field modeling in image analysis
Markov random field modeling in image analysis
A Multiphase Level Set Framework for Image Segmentation Using the Mumford and Shah Model
International Journal of Computer Vision
Finite-Element Methods for Active Contour Models and Balloons for 2-D and 3-D Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
X-means: Extending K-means with Efficient Estimation of the Number of Clusters
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
Automatic 3D Shape Reconstruction of Bones Using Active Nets Based Segmentation
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 1
Pattern Recognition and Machine Learning (Information Science and Statistics)
Pattern Recognition and Machine Learning (Information Science and Statistics)
Facial Component Extraction by Cooperative Active Nets with Global Constraints
ICPR '96 Proceedings of the 13th International Conference on Pattern Recognition - Volume 2
Parametric active membrane for segmentation of multiple objects in an image
Pattern Recognition
Multiple objects segmentation with fuzzy rule-base trained topology adaptive active membrane
Proceedings of the Seventh Indian Conference on Computer Vision, Graphics and Image Processing
MICCAI'10 Proceedings of the 13th international conference on Medical image computing and computer-assisted intervention: Part III
Fuzzy logic approaches to structure preserving dimensionality reduction
IEEE Transactions on Fuzzy Systems
Snakes, shapes, and gradient vector flow
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
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In this paper we have used conditional random field based learning scheme to differentiate the spectral signature of the objects and background in a scene. The overall objective is to segment multiple objects in a poorly contrasted scene. The primary tool for segmentation is a region based active membrane which evolves under image based external energy. The learning scheme helps in splitting the active membrane for segmenting multiple objects and integrates the topology adaptive property of the active membrane with the architecture and evolution of the membrane. The proposed approach is tested in a challenging application domain of estimation of sizes of oil sand rocks.