The independent components of characters are ‘strokes’

What are the natural features of hand-written characters and how to arrive at them automatically? We apply independent components analysis on hand-written characters. Independent components analysis extracts the underlying statistically independent signals from a mixure of them. We expect strokes to be the independent components of handwritten characters. Our findings show that stroke-like features emerge as a result of the analysis confirming the above intuition. This finding is significant since it gives an automatic procedures for extracting stroke-like features from multilingual character data sets. We use these features for handwritten digit recognition using a very simple classifier. The classifier is chosen to be simple so that the quality of input feature set can be evaluated. The recognition results indicate that the features arrived at by independent component analysis are useful.