Segmentation-driven offline handwritten Chinese and Arabic script recognition
SACH'06 Proceedings of the 2006 conference on Arabic and Chinese handwriting recognition
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This paper presents a lexicon based method for Chinese string recognition. In this method, we recognize a Chinese string image as a whole by matching it against lexicons in a database. We first over-segment the input line image into a series of radicals and recognize all the possible radical combinations. We then search for candidate lexicons in a given database according to the extracted keywords. Each lexicon is compared with the image to find the best match between the radicals and the given string by substring alignment. In this process, the segmentation and recognition results are determined synchronously. Our method is tested on 500 handwritten images of Chinese address and achieves a correct rate of 87% in address match.