Title :
Automatic snake contours for the segmentation of multiple objects
Author :
Cheng-Hung Chuang ; Lie, Wen-Nuizg
Author_Institution :
Dept. of Electr. Eng., Nat. Chung Cheng Univ., Chia-Yi, Taiwan
Abstract :
This paper presents an automatic snake algorithm for the segmentation of multiple objects. Traditional snake algorithms are often short of the capability in processing multi-objects or required to have manually drawn initial contours. Our algorithm is composed of two phases: (1) the active point phase and (2) the active contour phase. In the first phase, grid points distributed everywhere in the image are moved to form clusters near object boundaries. These clustered active points are then processed to obtain polygons as initial snake contours in the second phase. Both the dynamics of active points and deformation of active contours are based on the gradient vector flow (GVF) field with a greedy search strategy. Experiments show good performance of our algorithm in segmenting multiple, concave, as well as overlapped objects, even in noisy images
Keywords :
gradient methods; image segmentation; pattern clustering; random noise; search problems; active contour phase; active contours; active point phase; automatic snake contours; clusters; concave objects; dynamics; gradient vector flow field; greedy search strategy; grid points; multi-objects; multiple objects; object boundaries; overlapped objects; polygons; segmentation of multiple objects; snake algorithms; Active contours; Clustering algorithms; Computational complexity; Convergence; Equations; Greedy algorithms; Image edge detection; Image segmentation; Object detection; Potential energy;
Conference_Titel :
Circuits and Systems, 2001. ISCAS 2001. The 2001 IEEE International Symposium on
Conference_Location :
Sydney, NSW
Print_ISBN :
0-7803-6685-9
DOI :
10.1109/ISCAS.2001.921089