Title :
Dynamic Directional Convolution Vector Field for Active Contour Models
Author :
Wang, Gang ; Liang, Jianming ; Wang, Yang
Author_Institution :
Sch. of Inf. Sci. & Eng., Northeastern Univ., Shenyang, China
Abstract :
In this paper, we propose a novel dynamic external force for snakes named dynamic directional convolution vector field (DDCVF). It makes use of the gradients of gray-level images and defines positive and negative boundaries in horizontal and vertical directions, respectively. Furthermore, DDCVF is calculated by convolving the user-defined vector field kernel with the edge map generated from the image in the two directions separately. Experimental results show that the DDCVF snake has a large capture range and better robustness to disturbance and initialization.
Keywords :
convolution; edge detection; gradient methods; image segmentation; DDCVF snake; active contour model; dynamic directional convolution vector field; dynamic external force; edge map; gray level image; negative boundaries; positive boundaries; user defined vector field kernel; Information services; Internet; Active contour models; Dynamic directional convolution vector field; Gradient vector flow;
Conference_Titel :
Internet Computing & Information Services (ICICIS), 2011 International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4577-1561-7
DOI :
10.1109/ICICIS.2011.33
