On active contour models and balloons
CVGIP: Image Understanding
A fast algorithm for active contours and curvature estimation
CVGIP: Image Understanding
Shape Modeling with Front Propagation: A Level Set Approach
IEEE Transactions on Pattern Analysis and Machine Intelligence
International Journal of Computer Vision
A contour detection method: initialization and contour model
Pattern Recognition Letters
Image segmentation by reaction-diffusion bubbles
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
A Statistical Approach to Snakes for Bimodal and Trimodal Imagery
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Geodesic Active Regions for Supervised Texture Segmentation
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Snakes, shapes, and gradient vector flow
IEEE Transactions on Image Processing
Force field analysis snake: an improved parametric active contour model
Pattern Recognition Letters
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'Snakes' are an effective approach to image segmentation. However, self-looping is a common problem that can cause segmentation failure of snakes in the recovery of highly irregular object shapes, such as in long tube-like shapes, sharp corners or deep concave/convex shapes. This paper introduces the notion of loop-free snakes that can quickly and effectively remove all self-loops during their evolution, consistently deforming and conforming to complicated shapes of target objects. The proposed snakes are less sensitive to their initial contour condition, are resilient to their inconsistent parameter settings in a Certain degree and require low computing cost in terms of both computation time and storage. Experiments are conducted to segment real images with encouraging results.