Abstract
Segmentation of handwritten touching characters is an important task in optical character recognition (OCR). A new model-based segmentation algorithm is proposed for handwritten numeral strings. This method is based on the boundary analysis of the numeral strings, where a set of new features are extracted. These features can be used for global interpretation of the boundary structures. Various models are then constructed for the common touching patterns, which can increase the reliability of the segmentation and reduce the segmentation time. While we concentrate on the description of the segmentation method for two single-touching digits in this paper, our method can be extended to segmentation of touching digits in other situations.
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