By Topic

Affine Invariant Dynamic Time Warping and its Application to Online Rotated Handwriting Recognition

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Yu Qiao ; University of Electro-Communications,1-5-1 Chofugaoka, Chofu, Tokyo, 182-8585, Japan ; M. Yasuhara

Dynamic Time Warping (DTW) has been widely used to align and compare two sequences. DTW can efficiently deal with local warp or deformation between sequences. However, it can’t take account of affine transformation of sequences, such as rotation, shift and scale. This paper introduces a novel Affine Invariant Dynamic Time Warping (AI-DTW) method, which tries to deal with the affine transformation and sequence alignment in a unified framework. We propose an iterative algorithm to estimate the optimal transformation matrix and warping path by mutually updating them. Recognition experiments on the online rotated handwritten data illustrated that the AI-DTW achieves a recognition rate of 95.54%, which is significantly higher than that (65.87%) of the classical DTW method.

Published in:

18th International Conference on Pattern Recognition (ICPR'06)  (Volume:2 )

Date of Conference:

20-24 Aug. 2006