Active contours without edges Export

@article{citeulike:527571, abstract = {We propose a new model for active contours to detect objects in a given image, based on techniques of curve evolution, Mumford-Shah (1989) functional for segmentation and level sets. Our model can detect objects whose boundaries are not necessarily defined by the gradient. We minimize an energy which can be seen as a particular case of the minimal partition problem. In the level set formulation, the problem becomes a \“mean-curvature flow\”-like evolving the active contour, which will stop on the desired boundary. However, the stopping term does not depend on the gradient of the image, as in the classical active contour models, but is instead related to a particular segmentation of the image. We give a numerical algorithm using finite differences. Finally, we present various experimental results and in particular some examples for which the classical snakes methods based on the gradient are not applicable. Also, the initial curve can be anywhere in the image, and interior contours are automatically detected}, author = {Chan, T. F. and Vese, L. A.}, booktitle = {Image Processing, IEEE Transactions on}, citeulike-article-id = {527571}, citeulike-linkout-0 = {http://dx.doi.org/10.1109/83.902291}, citeulike-linkout-1 = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=902291}, doi = {10.1109/83.902291}, journal = {Image Processing, IEEE Transactions on}, keywords = {image-search, mitchell-group, shape}, number = {2}, pages = {266--277}, posted-at = {2007-11-04 22:14:42}, priority = {2}, title = {Active contours without edges}, url = {http://dx.doi.org/10.1109/83.902291}, volume = {10}, year = {2001} }

TY - JOUR ID - citeulike:527571 L3 - citeulike-article-id:527571 N2 - We propose a new model for active contours to detect objects in a given image, based on techniques of curve evolution, Mumford-Shah (1989) functional for segmentation and level sets. Our model can detect objects whose boundaries are not necessarily defined by the gradient. We minimize an energy which can be seen as a particular case of the minimal partition problem. In the level set formulation, the problem becomes a “mean-curvature flow”-like evolving the active contour, which will stop on the desired boundary. However, the stopping term does not depend on the gradient of the image, as in the classical active contour models, but is instead related to a particular segmentation of the image. We give a numerical algorithm using finite differences. Finally, we present various experimental results and in particular some examples for which the classical snakes methods based on the gradient are not applicable. Also, the initial curve can be anywhere in the image, and interior contours are automatically detected IS - 2 JF - Image Processing, IEEE Transactions on EP - 277 TI - Active contours without edges VL - 10 T2 - Image Processing, IEEE Transactions on SP - 266 KW - image-search KW - mitchell-group KW - shape AU - Chan, TF AU - Vese, LA PY - 2001/// UR - http://dx.doi.org/10.1109/83.902291 ER -