Title :
Robust topology-adaptive snakes for image segmentation
Author :
Ji, Lilian ; Yan, Hong
Author_Institution :
Sch. of Electr. & Inf. Eng., Sydney Univ., NSW, Australia
Abstract :
This paper introduces a robust topology-adaptive snake to extend the topological adaptability and flexibility of "snakes". Based on the attractable snake model, three embedded schemes, the robust self-looping process scheme, efficient contour-merging scheme and adaptive interpolation scheme, are proposed. The new snake model is able to: evolve consistently towards its target objects, handle topological changes (i.e., splitting or merging) automatically when necessary and conform to more complicated geometries and topologies, without restrictive requirements on the initial conditions of the snake model (including its parameter settings and its initial contour status) or on its deformation movement. The experiment results using the proposed model for various images are presented
Keywords :
adaptive signal processing; image segmentation; interpolation; topology; adaptive interpolation; contour-merging; embedded schemes; image segmentation; self-looping process; topological adaptability; topological flexibility; topology-adaptive snakes; Active contours; Australia; Deformable models; Image analysis; Image segmentation; Merging; Robustness; Shape; Solid modeling; Topology;
Conference_Titel :
Image Processing, 2001. Proceedings. 2001 International Conference on
Conference_Location :
Thessaloniki
Print_ISBN :
0-7803-6725-1
DOI :
10.1109/ICIP.2001.958614