A variational level set approach to multiphase motion
Journal of Computational Physics
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
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Geometric Level Set Methods in Imaging,Vision,and Graphics
Geometric Level Set Methods in Imaging,Vision,and Graphics
Computer Vision and Image Understanding
Energy minimization based segmentation and denoising using a multilayer level set approach
EMMCVPR'05 Proceedings of the 5th international conference on Energy Minimization Methods in Computer Vision and Pattern Recognition
IEEE Transactions on Image Processing
Unsupervised Variational Image Segmentation/Classification Using a Weibull Observation Model
IEEE Transactions on Image Processing
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A novel variational level set method for multiple object detection is presented, which uses n -1 level set functions for n -1 objects and the background without overlapping and vacuum problems. The energy functional includes three parts. The first part is a parametric region-based model via generic image noise distributions, the second part is the classic edge-based model, the third part is a term used to enforce the constraints of level set functions as signed distance functions. Characteristic functions for region partitioning are written in a unified form using Heaviside functions of level set functions. Some intermediate terms in evolution equations are extracted in a unified form for simplification of expressions and computation efficiency. The corresponding semi-implicit schemes are derived and used to some examples for segmentation of synthetic and real images to validate the method suggested in this paper.