TY - GEN
T1 - Analytical dynamic programming matching
AU - Uchida, Seiichi
AU - Hokahori, Satoshi
AU - Feng, Yaokai
N1 - Copyright:
Copyright 2018 Elsevier B.V., All rights reserved.
PY - 2012
Y1 - 2012
N2 - 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.
AB - 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.
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U2 - 10.1007/978-3-642-33863-2_10
DO - 10.1007/978-3-642-33863-2_10
M3 - Conference contribution
AN - SCOPUS:84867734629
SN - 9783642338625
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 92
EP - 101
BT - Computer Vision, ECCV 2012 - Workshops and Demonstrations, Proceedings
PB - Springer Verlag
T2 - 12th European Conference on Computer Vision, ECCV 2012
Y2 - 7 October 2012 through 13 October 2012
ER -