Handwritten numeral string recognition with stroke grouping

In this paper a framework for off-line handwritten numeral string recognition based on stroke grouping is proposed. In our approach, strokes are aligned into a sequence of strokes and then a segmentation process is performed to partition strokes in the sequence into possible-digits, that is, groups of strokes which may be a digit. As a result of stroke grouping, grouping-hypotheses, which imply possible segmentation, are generated. An input numeral string is recognized by a dynamic programming scheme, in which the best grouping-hypothesis with maximum matching score is chosen. The framework also provides a systematic way of reducing computational complexity by embedding external knowledge into the framework. The experimental results to evaluate the proposed framework are shown.