On-line cursive hangul recognition that uses DP matching to detect key segmentation points

摘要

As a means to perform on-line recognition of cursive Korean characters, called hanguls, we describe a structural analysis type algorithm that searches globally for key points of segmentation on a character unit level and can cope with large variations in stroke shape and position. This “segmentation points search” is systematically performed by a two-level dynamic programming (DP) matching algorithm in conjunction with syntax control of hangul composition characteristics. Fine discrimination for phonemes and characters is effectively realized using mutual information among strokes. Experiments demonstrate computational feasibility and that the proposed approach provides high recognition and segmentation ability.