Fronts propagating with curvature-dependent speed: algorithms based on Hamilton-Jacobi formulations
Journal of Computational Physics
IAPR Proceedings of the international workshop on Visual form: analysis and recognition
Shape Modeling with Front Propagation: A Level Set Approach
IEEE Transactions on Pattern Analysis and Machine Intelligence
International Journal of Computer Vision
A shock grammar for recognition
CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
A Common Framework for Curve Evolution, Segmentation and Anisotropic Diffusion
CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
Gradient flows and geometric active contour models
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Image segmentation by reaction-diffusion bubbles
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Symmetry Maps of Free-Form Curve Segments via Wave Propagation
International Journal of Computer Vision - Special Issue on Computational Vision at Brown University
Hierarchical Shape Decomposition via Level Sets
ISMM '09 Proceedings of the 9th International Symposium on Mathematical Morphology and Its Application to Signal and Image Processing
From a modified ambrosio-tortorelli to a randomized part hierarchy tree
SSVM'11 Proceedings of the Third international conference on Scale Space and Variational Methods in Computer Vision
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Abstract: In recent years, curve evolution has been applied to smoothing of shapes and shape analysis with considerable success, especially in biomedical image analysis. The multiscale analysis provides information regarding parts of shapes, their axes or centers and shape skeletons. Here, the authors show that the level sets of an edge-strength function provide essentially the same shape analysis as provided curve evolution. The new method has several advantages over the method of curve evolution. Since the governing equation is linear, the implementation is simpler and faster. The same equation applies to problems of higher dimension. An important advantage is that unlike the method of curve evolution, the new method is applicable to shapes which may have junctions such as triple points. The edge-strength may be calculated from raw images without first extracting the shape outline. Thus the method can be applied to raw images. The method provides a way to approach the segmentation problem and shape analysis within a common integrated framework.