Project Reading 7: A study on the use of 8-directional features for online handwritten Chinese character recognition

Citation

Bai, Zhen-Long, and Qiang Huo. "A study on the use of 8-directional features for online handwritten Chinese character recognition." Document Analysis and Recognition, 2005. Proceedings. Eighth International Conference on. IEEE, 2005.

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Summary

This paper presents a new way for Chinese Character Recognition using directional features only. The input sketch is passed through some preprocessing steps. These steps include linear size normalization, adding imaginary strokes, nonlinear shape normalization, equidistance resampling, and smoothing. After these pre processing step a 64x64 normalized character sample is obtained. Then at 8x8 uniformly sampled location are computed using a filter similar to Gaussian envelop of a Gabor filter. Then 8 directional features are computed from each online trajectory point. This gives a total vector of 512 data points which are then used to do the classification. The system is tested extensively on 3755 level-1 Chinese characters in GB2312-80 standard.

Discussion

The overall flowchart of the process described above is shown below:

The authors use two simple character classifiers at the classification step. The first one is a maximum discriminant function based classifier with a single prototype. The prototype is the mean of the training feature vectors, and the discriminant function is the negative Euclidean distance between a testing feature vector and the prototype feature vector.