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This paper presents an approach based on character recognition to searching for keywords in on-line handwritten Japanese text. It employs an on-line character classifier and an off-line classifier or a combined classifier, which produce recognition candidates, and it searches for keywords in the lattice of candidates. It integrates scores to individually recognize characters and their geometric context. We use quadratic discriminant function(QDF) or support vector machines(SVM) models to evaluate the geometric features of individual characters and the relationships between characters. This paper also presents an approach based on feature matching that employs on-line or off-line features. We evaluate three recognition-based methods, two feature-matching-based methods, as well as ideal cases of the latter and concluded that the approach based on character recognition outperformed that based on feature matching. key words: digital ink search, geometric context, character recognition, features matching

Digital Ink Search Based on Character-Recognition Candidates Compared with Feature-Matching-Based Approach