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| Structural Recognition of PDF Academic Literature Based on Computer Vision |
| Yu Fengchang, Lu Wei |
| School of Information Management, Wuhan University, Wuhan 430072 |
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Abstract Portable Document Format (PDF) documents play an important role in the publication of academic electronic literature. However, owing to the technical and structural complexities of PDF documents, they cannot be directly read by digital devices, which in turn can hinder research studies based on academic electronic literature. Hence, this paper proposes a method based on computer vision for the structural recognition of PDF documents. The proposed method, supplemented by a heuristic algorithm, maps graphic objects and text objects present in the PDF files of academic documents and thereby obtains geometric and text attributes of the file objects. The proposed algorithm can identify the category of a PDF object for determining the physical and logical structures of a PDF document. Conventional PDF analysis methods require a significant amount of artificial feature construction and large-scale lexical corpus training and cannot identify formulae and tables. The proposed method can overcome the aforementioned shortcomings and can successfully perform full-text extraction and structural recognition of ACL data collections.
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Received: 26 September 2018
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