Fronts propagating with curvature-dependent speed: algorithms based on Hamilton-Jacobi formulations
Journal of Computational Physics
Shape Modeling with Front Propagation: A Level Set Approach
IEEE Transactions on Pattern Analysis and Machine Intelligence
Flux Maximizing Geometric Flows
IEEE Transactions on Pattern Analysis and Machine Intelligence
A New Active Contour Method Based on Elastic Interaction
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Snakes, shapes, and gradient vector flow
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
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Performing segmentation of narrow, elongated structures with low contrast boundaries is a challenging problem. Boundaries of these structures are difficult to be located when noise exists or intensity of objects and background is varying. Using the active contour methods, this paper proposes a new vector field for detection of such structures. In this paper, unlike other work, object boundaries are not defined by intensity gradient but statistics obtained from a set of filters applied on an image. The direction and magnitude of edges are estimated such that the minimal weighted local variance condition is satisfied. This can effectively prevent contour leakage and discontinuity by linking disconnected boundaries with coherent orientation. It is experimentally shown that our method is robust to intensity variation in the image, and very suitable to deal with images with narrow structures and blurry edges, such as blood vessels.