Handwritten Chinese Character Recognition Using Spatial Gabor Filters and Self-Organizing Feature Maps

So far the bottleneck of Chinese character recognition, especially handwritten character recognition, still lies in the effectiveness of featureextraction to cater for various distortions and position shifting. In ths paper, a novel method is proposed by applying a set of Gabor spatial filters with different directions and spatial frequencies to character images, in an effort to reach the optimum trade-off between feature stability and feature localization. While a classic self-organizing map is used for unsupervised clustering feature codes, a multi-staged LVQ with a fuzzy judgement unit is applied for the final recognition on the feature mapping result.