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Published Articles >> Table of Contents >> Abstract
November 1995 (Vol. 17, No. 11)
pp. 1084-1090
Deformable Contours: Modeling and Extraction
Kok F. Lai
Roland T. Chin
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DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/34.473235
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Abstract—This paper considers the problem of modeling and extracting arbitrary deformable contours from noisy images. We propose a global contour model based on a stable and regenerative shape matrix, which is invariant and unique under rigid motions. Combined with Markov random field to model local deformations, this yields prior distribution that exerts influence over a global model while allowing for deformations. We then cast the problem of extraction into posterior estimation and show its equivalence to energy minimization of a generalized active contour model. We discuss pertinent issues in shape training, energy minimization, line search strategies, minimax regularization and initialization by generalized Hough transform. Finally, we present experimental results and compare its performance to rigid template matching.
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 References
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[1] T. Poggio and V. Torre,“Ill-posed problems and regularization analysis in early vision,” Proc. AARPA Image Understanding Workshop, pp. 257-263, 1984.
[2] D.H. Ballard,“Generalizing the Hough transform to detect arbitrary shapes,” Pattern Recognition, vol. 13, pp. 111-122, 1981.
[3] Kass,A. Witkin,, and D. Terzopoulos,“Snakes: Active contour models,” Proc. First Int’l Conf. Cmputer Vision, pp. 259-269, 1987.
[4] A.L. Yuille, D.S. Cohen, and P.W. Hallinan, "Feature Extraction from Faces Using Deformable Templates," Proc. Computer Vision and Pattern Recognition,San Diego, June 1989.
[5] L.H. Staib and J.S. Duncan, “Boundary Finding with Parametrically Deformable Models,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 14, no. 11, pp. 1,061-1,075, Nov. 1992.
[6] J. Subrahmonia,J.D. karen,, and D.B. Cooper,“Bayesian method for the use of implicit polynomials and algebraic invariants in practical computer vision,” Curves and Surfaces in Computer Vision and Graphics 3, pp. 104-117, 1992.
[7] G.E. Hinton,C.K.I. Williams,, and M.D. Revow,“Adaptive elastic models for hand-printed character recognition,” Neural Information Processing Systems, J.E. Moody, et al., eds., vol. 4, pp. 512-519, 1992.
[8] A. Blake, R. Curwen, and A. Zisserman, "Affine-Invariant Contour Tracking with Automatic Control of Spatiotemporal Scale," IEEE Proc. Fourth Int'l Conf. Computer Vision, pp. 66-75,Berlin, Germany, May 1993.
[9] K.F. Lai and R.T. Chin,“On regularization, formulation, and initialization of the active contour models (snakes),” Asian Conf. Computer Vision, pp. 542-545, 1993.
[10] A.A. Amini,T.E. Weymouth,, and R.C. Jain,“Using dynamic programming for solving variational problems in vision,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 12, no. 9, pp. 855-867, 1990.
[11] D.J. Williams and M. Shah,“A fast algorithm for active contours and curvature estimation,” Computer Vision, Graphics, Image Processing, vol. 55, pp. 14-26, 1992.
[12] W.E.L. Grimson and D.P. Huttenlocher, "On the Sensitivity of the Hough Transform for Object Recognition," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 12, no. 3, pp. 255-274, Mar. 1990.
[13] W.L. Grimson,D.P. Huttenlocher,, and T.D. Alter,“Recognizing 3D objects from 2D images: An error analysis,” Proc. CVPR 1992, pp. 316-321.
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 Additional Information
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Index Terms- Deformable model, rigid template, snake, active contour, boundary extraction.
Citation:
Kok F. Lai, Roland T. Chin,
"Deformable Contours: Modeling and Extraction,"
IEEE Transactions on Pattern Analysis and Machine Intelligence,
vol. 17,
no. 11,
pp. 1084-1090,
Nov.,
1995
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