TY - GEN
T1 - Adaptive vector flow for active contour model
AU - Zhang, Qi
AU - Liu, Lixiong
AU - Liu, Bao
PY - 2012
Y1 - 2012
N2 - A novel external force for active contours, called as adaptive vector flow (AVF), is proposed in this paper. Based on analyzing the diffusion mechanism of gradient vector flow (GVF), it is found that GVF is difficult to preserve weak edges and enter long and thin concavities. In AVF, we replace the isotropic smoothness term of GVF by an adaptive anisotropic one and adjust the diffusion speed in tangent and normal directions by the local features of the images. Experimental results on synthetic and real images show that, compared with the GVF snake, the AVF snake has better performance and properties.
AB - A novel external force for active contours, called as adaptive vector flow (AVF), is proposed in this paper. Based on analyzing the diffusion mechanism of gradient vector flow (GVF), it is found that GVF is difficult to preserve weak edges and enter long and thin concavities. In AVF, we replace the isotropic smoothness term of GVF by an adaptive anisotropic one and adjust the diffusion speed in tangent and normal directions by the local features of the images. Experimental results on synthetic and real images show that, compared with the GVF snake, the AVF snake has better performance and properties.
KW - Active Contour
KW - Adaptive Vector Flow
KW - Gradient Vector Flow
KW - Image Segmentation
UR - https://www.scopus.com/pages/publications/84867115868
U2 - 10.1007/978-3-642-33506-8_16
DO - 10.1007/978-3-642-33506-8_16
M3 - Conference contribution
AN - SCOPUS:84867115868
SN - 9783642335051
T3 - Communications in Computer and Information Science
SP - 121
EP - 128
BT - Pattern Recognition - Chinese Conference, CCPR 2012, Proceedings
T2 - 2012 5th Chinese Conference on Pattern Recognition, CCPR 2012
Y2 - 24 September 2012 through 26 September 2012
ER -