Segmentation and Classification of Cell Cycle Phases in Fluorescence Imaging
MICCAI '09 Proceedings of the 12th International Conference on Medical Image Computing and Computer-Assisted Intervention: Part II
Depth Data Improves Skin Lesion Segmentation
MICCAI '09 Proceedings of the 12th International Conference on Medical Image Computing and Computer-Assisted Intervention: Part II
Fuzzy energy-based active contours
IEEE Transactions on Image Processing
Fast graph partitioning active contours for image segmentation using histograms
Journal on Image and Video Processing
On the Length and Area Regularization for Multiphase Level Set Segmentation
International Journal of Computer Vision
Shape-based image segmentation through photometric stereo
Computer Vision and Image Understanding
A Quaternion Framework for Color Image Smoothing and Segmentation
International Journal of Computer Vision
Embedding Gestalt laws on conditional random field for image segmentation
ISVC'11 Proceedings of the 7th international conference on Advances in visual computing - Volume Part I
MDS-based segmentation model for the fusion of contour and texture cues in natural images
Computer Vision and Image Understanding
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Variational cost functions that are based on pairwise similarity between pixels can be minimized within level set framework resulting in a binary image segmentation. In this paper we extend such cost functions and address multi-region image segmentation problem by employing a multi-phase level set framework. For multi-modal images cost functions become more complicated and relatively difficult to minimize. We extend our previous work, proposed for background/foreground separation, to the segmentation of images in more than two regions. We also demonstrate an efficient implementation of the curve evolution, which reduces the computational time significantly. Finally, we validate the proposed method on the Berkeley Segmentation Data Set by comparing its performance with other segmentation techniques.