A fuzzy approach for segmentation of touching characters

The problem of correctly segmenting touching characters is an hard task to solve. In the recent years, many methods and algorithms have been proposed without achieving a comprehensive solution. In this paper, a novel method based on fuzzy logic is studied. The proposed method combines three features of touching characters that in other studies have been exploited one at a time. The strategy is based on a 3–input/1– output fuzzy inference system with fuzzy rules specifically optimized for segmenting touching characters in the case of latin printed and handwritten characters. The system performances are illustrated and supported by numerical examples that show an optimal capability of segmenting touching characters. Moreover, numerical results suggest that the method can be applied to many different datasets of characters by means of a convenient tuning of the fuzzy sets and rules.