Sketched symbol recognition using zernike moments (2004)
| Venue: | International Conference on Pattern Recognition |
| Citations: | 20 - 0 self |
BibTeX
@INPROCEEDINGS{Hse04sketchedsymbol,
author = {Heloise Hse and A. Richard Newton},
title = {Sketched symbol recognition using zernike moments},
booktitle = {International Conference on Pattern Recognition},
year = {2004},
pages = {367--370}
}
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Abstract
In this paper, we present an on-line recognition method for hand-sketched symbols. The method is independent of stroke-order,-number, and-direction, as well as invariant to rotation, scaling, and translation of symbols. Zernike moment descriptors are used to represent symbols and three different classification techniques are compared: Support Vector Machines (SVM), Minimum Mean Distance (MMD), and Nearest Neighbor (NN). We have obtained 97 % accuracy rate on a dataset consisting of 7,410 sketched symbols using Zernike moment features and a SVM classifier. This method has been implemented in a software recognition package, HHreco [7]. 1.
