Resolving Ambiguity in Segmenting Touching Characters

Abstract

This paper presents an efficient and powerful character segmentation method which enables touching characters in a document to be read accurately at high speed. The character segmentation phase extracts characters from a text line. Connected components in a text line image may have to be segmented or combined to form recognizable characters. For example, the character ‘i’ is formed by combining two components. Touching characters are segmented to identify each character. Segmenting touching characters is an open problem, whose solution would advance the field. Touching characters have several candidates for their break position, which are then confirmed by recursive segmentation and recognition, and finally by the determination of the linguistic context. There are several possible candidates at each stage. For example, several candidates for the break position of touching characters are nominated. Any segmented area might possibly fit several alternative characters. Therefore, an efficient resolution of ambiguity at each stage is significantly critical and indispensable for practical text reading. The authors’ approach is based on knowledge about character composition (e.g. an ‘m’ is like a combination of an ‘r’ and an ‘n’), as well as knowledge about omni-fonts. Knowledge about character composition compresses the number of recursive segmentation and recognition.