Distorted character recognition is a difficult but inevitable problem in hand-printed character recognition. In this paper, we propose a character recognition method using elastic models for recognizing cursive characters with intricate structure. The models are fitted to unknown input patterns by applying the EM algorithm to minimize a measure of fittness. To avoid falling into local minima, multiresolutional approach is introduced. Moreover, nonlinear transformation is adopted to realize more flexible matching. Experiments performed on Japanese characters show effectiveness of the proposed method.
|Number of pages||4|
|Journal||Proceedings - International Conference on Pattern Recognition|
|Publication status||Published - 2000 Dec 1|
ASJC Scopus subject areas
- Computer Vision and Pattern Recognition