Robust and Highly Customizable Recognition of On-Line Handwritten Japanese Characters
ICPR '96 Proceedings of the International Conference on Pattern Recognition (ICPR '96) Volume III-Volume 7276 - Volume 7276
ICASSP '01 Proceedings of the Acoustics, Speech, and Signal Processing, 2001. on IEEE International Conference - Volume 03
HBF49 feature set: A first unified baseline for online symbol recognition
Pattern Recognition
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This paper presents a study of using 8-directional features for online handwritten Chinese character recognition. Given an online handwritten character sample, a series of processing steps, including linear size normalization, adding imaginary strokes, nonlinear shape normalization, equidistance resampling, and smoothing, are performed to derive a 64脳64 normalized online character sample. Then, 8-directional features are extracted from each online trajectory point, and 8 directional pattern images are generated accordingly, from which blurred directional features are extracted at 8 脳 8 uniformly sampled locations using a filter derived from the Gaussian envelope of a Gabor filter. Finally, a 512-dimensional vector of raw features is formed. Extensive experiments on the task of recognizing 3755 level-1 Chinese characters in GB2312-80 standard are performed to compare and discern the best setting for several algorithmic choices and control parameters. The effectiveness of the studied approach is confirmed.