Abstract
In this paper, we show that the truly two-dimensional elastic image matching problem can be solved analytically using dynamic programming (DP) in polynomial time if the problem is formulated as a maximum a posteriori problem using Gaussian distributions for the likelihood and prior. After giving the derivation of the analytical DP matching algorithm, we evaluate its performance on handwritten character images containing various nonlinear deformations, and compare other elastic image matching methods. © 2012 Springer-Verlag.
Cite
CITATION STYLE
Uchida, S., Hokahori, S., & Feng, Y. (2012). Analytical dynamic programming matching. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7583 LNCS, pp. 92–101). Springer Verlag. https://doi.org/10.1007/978-3-642-33863-2_10
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