Cherry Blossom: A System for Japanese Character Recognition

A general purpose Japanese character recognition system, Cherry Blossom, has been developed at CEDAR in past years. It is designed to recognize Japanese document images in low resolution or with poor print quality. The system includes modules for page skew correction, document segmentation, text segmentation, character recognition and postprocessing. The API code for each module has been developed so that each module can be tested as a standalone program or can be called in large application systems such as a document indexing and retrieval system. In the character recognition module, two classi cation methods, the nearest-neighbor classi er and the subspace method, have been integrated in an efcient way. The speed of character recognition is about six characters per second from the original one character per second. New techniques, including dynamic feature selection, incremental nearest prototype search and visual similarity analysis, have been developed to speed up character classi cation while keeping high accuracy. A linguistic postprocessing module improves the accuracy of character recognition by exploiting linguistic context. It was trained on a Japanese text corpus with above 70 mil-