Authors’ names are a critical bibliographic element when searching or browsing academic articles stored in digital libraries. However, extracting such bibliographic data from printed documents requires human intervention; it is therefore not cost-effective, even using various document image-processing techniques such as Optical Character Recognition (OCR). In this paper, we describe an automatic authors’ names extraction method for academic articles scanned with OCR mark-up. The proposed method first extracts authors’ blocks, which include assumed author/delimiter characters based on layout analysis, and then uses a specifically designed Hidden Markov Model (HMM) for labeling the unsegmented character strings in the block as those of either an author or a delimiter. We applied the proposed method to Japanese academic articles. Results of these experiments showed that the proposed method correctly extracted more than 99% of authors’ blocks with manual tuning; the proposed HMM correctly labeled more than 95% of the author name strings.
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