Abstract
The paper presents a new external force field for active contour model, which is called CGVF (Curvature Gradient Vector Flow). CGVF improves on classical GVF by simplifying the formulas and increasing the item of curvature, so that the edge information can be kept well and diffused more quickly. Several standard images are used to segmenting experiments, and the results show that CGVF has obvious advantages compared with GVF in the iteration number of force field, the evolvement number of curve and the accuracy of convergence. In particular, when the initial curve is far from the edge of object, the convergence will be more superior.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Kass, M., Withkin, A., Terzopoulos, D.: Snakes:Active contour models. Internat. J. Computer Vision, 321–331 (1988)
Osher, S., Sethian, J.A.: Fronts propagating with curvature dependent speed: algorithms based on Hamilton-Jacobi formulations. J. Comput. Phys 79, 12–49 (1988)
Amini, A.A., Weymouth, T.E., Jain, R.C.: Using dynamic programming for solving variational problems in vision. IEEE Trans. Pattern Anal. Machine Intell 12(9), 855–867 (1990)
Cohen, T.F.: On active contour models and balloons. Comput. Vision Graph. Image Process(Image Understanding) 53(2), 211–218 (1991)
Cohen, L.D., Cohen, I.: Finite-element methods for active contour models and balloons for 2-D and 3-D images. IEEE Trans. Pattern Anal. Machine Intell. 15, 1131–1147 (1993)
Malladi, R., Sethian, J.A., Vermuri, B.C.: Shape modeling with front propagation: a level set approach. Machine Intell. 17(2), 158–175 (1995)
Xu, C., Prince, J.L.: Gradient vector flow: A new external force model for snakes. In: IEEE Proc. Conf. on Computer Vision and Pattern Recognition, pp. 66–71 (1997)
Xu, C., Prince, J.L.: Snakes, shapes, and Gradient Vector flow. IEEE trans. Image Processing. 7, 359–369 (1998)
Xu, C., Prince, J.L.: Generalized gradient vector flow external forces for active contours. Signal Processing 71, 131–139 (1998)
Yuen, P.C., Feng, G.C., Zhou, J.P.: Contour detection method:Initialization and contour model. Pattern Recognition Letters 20, 141–148 (1998)
Jain, A., Zhong, Y., Dubuisson-Jolly, M.: Deformable template models: A review. Signal Processing 71, 109–129 (1998)
Caselles, V., Morel, J.-M., Sbert, C.: An axiomatic approach to image interpolation. IEEE trans. Image Processing 7(3), 376–386 (1998)
Sethian, J.A.: Level set methods and fast marching methods. Cambridge University Press, Cambridge (1999)
Zhong, Y., Jain, A.K., Dubuisson-Jolly, M.: Object tracking using deformable templates. IEEE Trans. Pattern Anal. Machiine Intell. 22, 544–549 (2000)
Park, J., Keller, J.M.: Snake on the watershed. IEEE Trans. Pattern Anal. Machine Intell. 23, 1201–1205 (2001)
Visen, N.S., Shashidhar, N.S., Paliwal, J., Jayas, D.S.: Identification and segmentation of occluding groups of grain kernels in a grain sample image. J. Agric. Eng. Res. 79(2), 159–166 (2001)
Chan, T.F., Vese, L.A.: Active contours without edges. IEEE Trans. Image Processing 10(2), 266–277 (2001)
Wang, Y.-C., Chou, J.-J.: Automatic segmentation of touching rice kernels with an active contour model. Transaction of ASAE 2004 47(5), 1803–1811 (2004)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Ning, J., Wu, C., Liu, S., Wen, P. (2006). A New Active Contour Model: Curvature Gradient Vector Flow. In: Narayanan, P.J., Nayar, S.K., Shum, HY. (eds) Computer Vision – ACCV 2006. ACCV 2006. Lecture Notes in Computer Science, vol 3851. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11612032_64
Download citation
DOI: https://doi.org/10.1007/11612032_64
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-31219-2
Online ISBN: 978-3-540-32433-1
eBook Packages: Computer ScienceComputer Science (R0)