Character pre-classification based on fuzzy typographical analysis

Abstract

This paper presents a new fuzzy-logic approach for character pre-classification which gives a precise way of calculating the baseline detection algorithm with tolerance analysis through analyzing the typographical structure of textual blocks. The other virtual reference lines are extracted from clustering techniques. In order to ensure character pre-classification correctly, a fuzzy-logic approach is used to assign a membership to each typographical category for ambiguous classes. The results prove that an improved character recognition rate can be achieved by means of typographical categorization. The fuzzy typographical analysis can correctly pre-classify characters and can efficiently process more than 10000 characters per second.