Extracting stroke errors from digital ink characters by beginning learners of Chinese as a foreign language based on accurate stroke matching

Abstract

The extraction of errors is an important aspect of Chinese character writing research. Stroke errors are the origins of most handwriting mistakes. Previous works have made some efforts on the types of errors extracted, while most of them are either preset by rules or deficient to include all types of stroke errors. For foreign students learning Chinese as a foreign language, especially beginners whose writing habits and characteristics are affected by ones of their native languages, methods by presetting are difficult to adopt. Therefore, this paper initiated from the data itself, proposes an adaptive approach to extract handwriting errors based on the result of the stroke matching which is accurate to sampling points in strokes. After the tagging list given as a matching index, the writing errors are adaptively extracted in different stroke errors of Chinese characters, including missing strokes, extra strokes, concatenated strokes, broken strokes, redundant strokes, incomplete strokes, the error of orientation and order. After serial experiments, the result indicates that the proposed approach is effective in extracting handwriting stroke errors.