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<Paper uid="P98-2152">
  <Title>Japanese OCR Error Correction using Character Shape Similarity and Statistical Language Model</Title>
  <Section position="2" start_page="0" end_page="0" type="abstr">
    <SectionTitle>
Abstract
</SectionTitle>
    <Paragraph position="0"> We present a novel OCR error correction method for languages without word delimiters that have a large character set, such as Japanese and Chinese.</Paragraph>
    <Paragraph position="1"> It consists of a statistical OCR model, an approximate word matching method using character shape similarity, and a word segmentation algorithm using a statistical language model. By using a statistical OCR model and character shape similarity, the proposed error corrector outperforms the previously published method. When the baseline character recognition accuracy is 90%, it achieves 97.4% character recognition accuracy.</Paragraph>
  </Section>
class="xml-element"></Paper>