Finding image distributions on active curves

Finding image distributions on active curves

Ayed, Ismail Ben and Mitiche, Amar and Salah, Mohamed Ben and Li, Shuo

Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition 2010

Abstract : This study investigates an active curve functional which measures a similarity between the distribution of an image feature on the curve and a model distribution learned a priori. The curve evolution equation resulting from the minimization of this contour-based functional can be viewed as a geodesic active contour with a variable stopping function. The variable stopping function depends on the distribution of image feature on the curve and, therefore, can deal with difficult cases where the desired boundary corresponds to very weak image transitions. We ran several experiments supported by quantitative performance evaluations over several examples of segmentation and tracking of the left ventricle inner and outer boundaries in cardiac magnetic resonance image sequences. The results are significantly more accurate than with region-based and edge-based functionals. ©2010 IEEE.