Abstract
In the paper, we attempt to develop a novel method to offer the possibility even for a non-expert to extract easily the contour of an object. A NURBS-HMM framework aiming at the interactive image contour extraction is proposed. We fit the initial points input by users with Non-Uniform Rational B-Spline(NURBS). Due to the local controllability of NURBS, the control points are considered as the states of Hidden Markov Model(HMM) framework, and the boundary features and uniformity along the boundary are integrated as the observations. The experimental results show the robustness of our method. As an interactive method, the method interacts with users in an efficient and comfortable way.
This is a preview of subscription content, log in via an institution to check access.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Kass, M., Witkin, A., Terzopoulos, D.: Snakes: Active contour models. IJCV 1, 321–331 (1988)
Cohen, L., Kimmel, R.: Global minimum for active contour models: A minimal path approach. IJCV 24, 57–78 (1997)
Blake, A., Isard, M.: The Active Contours book. Springer, Heidelberg (1998)
Reese, L.: Intelligent Paint:Region-Based Interactive Image Segmentation. Masters Thesis, Department of Computer Science, Brigham Young University (1999)
Falcao, A., Udupa, J.: User-steered image segmentation paradigms: Live-wire and live-lane. GMIP 60, 233–260 (1998)
Mortensen, E., Morse, B., Barrett, W., Udupa, J.K.: Adaptive boundary detection using live-wire two-dimensional dynamic programming. In: IEEE Proc. of Computers in Cardiology (1992)
Mortensen, E., Barrett, W.: Intelligent scissors for image composition. In: Proc. of Computer Graphics, SIGGRAPH (1995)
Chuang, Y.-Y., Curless, B., Salesin, D., Szeliski, R.: A bayesian approach to digital matting. In: Proc. IEEE Conf. Computer Vision and Pattern Recog. (2001)
Boykov, Y., Jolly, M.P.: Interactive graph cuts for optimal boundary and region segmentation of objects in nd images. In: ICCV (2001)
Li, Y., Sun, J., Tang, C.K., Shum, H.Y.: Lazy snapping. ACM Transactions on Graphics (2004)
Rother, C., Kolmogorov, V., Blake, A.: Interactive foreground extraction using iterated graph cuts. ACM Transactions on Graphics (2004)
Piegl, L., Shah, M.: The NURBS Book, 2nd edn. Springer, Heidelberg (1997)
Rabiner, L., Juang, B.: An introduction to hidden markov models. IEEE ASSP Mag. (1986)
Chen, Y., Rui, Y., Huang, T.: Jpdaf based hmm for real-time contour tracking. In: Proc. of the IEEE CVPR (2001)
Liang, K., Rajeswari, M., Khoo, B.: Free form shape representation using nurbs modeling. In: Proc. of the Int. CGVCV (2002)
Dijkstra, E.: A note on two problems in connection with graphs. Numerische Mathematic 1, 269–271 (1959)
Derrode, S., Pieczynski, W.: Sar image segmentation using generalized pairwise markov chains. SPIE’s International Symposium on Remote Sensing, 22–27 (2002)
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
Lei, D., Pan, C., Yang, Q., Shi, M. (2006). Interactive Contour Extraction Using NURBS-HMM. 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_86
Download citation
DOI: https://doi.org/10.1007/11612032_86
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)