Copyright and Licensing
Articles accepted for publication will be licensed under the Creative Commons BY-NC-SA. Authors must sign a non-exclusive distribution agreement after article acceptance.
On improved deformable template matching for polygonal objects
Keywords:
Deformable template, Orthogonal curve, Polygonal object, Matching, Genetic algorithmAbstract
In this paper, an improvement of deformable template matching algorithm for polygonal objects in grayscale images using two-dimensional deformable templates along orthogonal curves is presented. In the process of pre-computing extensions of the deformable template along orthogonal curves, the novel matching approach incorporates adapting knowledge-specific template discretization techniques appropriate for different polygonal objects and minimizing the improved internal and external energy terms containing inter-shape information of polygonal objects. In our application, this energy optimization problem of the deformable template is efficiently solved by a genetic algorithm (GA). Our algorithm has been successfully applied on synthetic images and real images. The experiment results show that the new approach provides more robust and accurate matching method.
Downloads
Download data is not yet available.
References
[1] H. D. Tagare, “Deformable 2-D template matching using orthogonal curves”, IEEE Trans on Medical Imaging. 1997, 16(1): 859-870.
[2] D. J. Kriegman and J. Ponce, “On recognizing and positioning curved 3-D objects from image contours”, IEEE Transactions on Pattern Analysis and Machine Intelligence, 1990, 12(12): 1127-1137.
[3] M. Kass, A. Witkin, and D. Terzopoulos, “Snakes: active contour models”, International Journal of Computer Vision, 1987, 1(4): 321-331.
[4] MP Dubuisson-Jolly, S. Lakshmanan, Anil K Jain, “Vehicle segmentation using deformable templates”,IEEE Transactions on Pattern Analysis and Machine Intelligence, 1996, 18 (3): 293-308.
[5] L. Kitchen, A. Rosenfeld, “Gray level corner detection”, Pattern Recognition Letters, 1982, 1: 95-102
[6] Claes Johnson, Numerical Solution of Partial Differential Equations by the Finite Element Method, Cambridge University Press, New York, 1987.
[7] C. Pozrikidis, Numerical Computation in Science and Engineering, Oxford University Press, New York, 1998.
[8] Michalewicz, Z., Genetic Algorithms + Data Structures = Evolution Programs, Berlin: Springer-Verlag, 1992.
[9] Davis, L., Handbook of Genetic Algorithms, New York: Van Nostrand Reinhold, 1991.
[2] D. J. Kriegman and J. Ponce, “On recognizing and positioning curved 3-D objects from image contours”, IEEE Transactions on Pattern Analysis and Machine Intelligence, 1990, 12(12): 1127-1137.
[3] M. Kass, A. Witkin, and D. Terzopoulos, “Snakes: active contour models”, International Journal of Computer Vision, 1987, 1(4): 321-331.
[4] MP Dubuisson-Jolly, S. Lakshmanan, Anil K Jain, “Vehicle segmentation using deformable templates”,IEEE Transactions on Pattern Analysis and Machine Intelligence, 1996, 18 (3): 293-308.
[5] L. Kitchen, A. Rosenfeld, “Gray level corner detection”, Pattern Recognition Letters, 1982, 1: 95-102
[6] Claes Johnson, Numerical Solution of Partial Differential Equations by the Finite Element Method, Cambridge University Press, New York, 1987.
[7] C. Pozrikidis, Numerical Computation in Science and Engineering, Oxford University Press, New York, 1998.
[8] Michalewicz, Z., Genetic Algorithms + Data Structures = Evolution Programs, Berlin: Springer-Verlag, 1992.
[9] Davis, L., Handbook of Genetic Algorithms, New York: Van Nostrand Reinhold, 1991.
Downloads
Published
2004-04-01
Issue
Section
Original Articles
License
How to Cite
[1]
“On improved deformable template matching for polygonal objects”, JCS&T, vol. 4, no. 01, pp. p. 20–25, Apr. 2004, Accessed: Jul. 08, 2025. [Online]. Available: https://journal.info.unlp.edu.ar/JCST/article/view/909
