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The problem of correctly segmenting touching characters is an hard task tosolve and it is of major relevance in pattern recognition. In the recent years,many methods and algorithms have been proposed; still, a definitive solution isfar from being found. In this paper, we propose a novel method based on fuzzylogic. The proposed method combines in a novel way three features forsegmenting touching characters that have been already proposed in other studiesbut have been exploited only singularly so far. The proposed strategy is basedon a 3--input/1--output fuzzy inference system with fuzzy rules specificallyoptimized for segmenting touching characters in the case of Latin printed andhandwritten characters. The system performances are illustrated and supportedby numerical examples showing that our approach can achieve a reasonable goodoverall accuracy in segmenting characters even on tricky conditions of touchingcharacters. Moreover, numerical results suggest that the method can be appliedto many different datasets of characters by means of a convenient tuning of thefuzzy sets and rules.

A fuzzy approach for segmentation of touching characters