Figure Metadata Extraction from Digital Documents

Academic papers contain multiple figures (information graphics) representing important findings and experimental results. Automatic data extraction from such figures and classification of information graphics is not straightforward and a well studied problem in document analysis cite{4275059}. Also,...

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Bibliographic Details
Published in2013 12th International Conference on Document Analysis and Recognition pp. 135 - 139
Main Authors Choudhury, Sagnik Ray, Mitra, Prasenjit, Kirk, Andi, Szep, Silvia, Pellegrino, Donald, Jones, Sue, Giles, C. Lee
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.08.2013
Subjects
Accuracy
Data mining
Feature extraction
information extraction
Layout
Libraries
metadata based figure search
Portable document format
Search engines
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Summary:Academic papers contain multiple figures (information graphics) representing important findings and experimental results. Automatic data extraction from such figures and classification of information graphics is not straightforward and a well studied problem in document analysis cite{4275059}. Also, very few digital library search engines index figures and/or associated metadata (figure caption) from PDF documents. We describe the very first step in indexing, classification and data extraction from figures in PDF documents - accurate automatic extraction of figures and associated metadata, a nontrivial task. Document layout, font information, lexical and linguistic features for figure caption extraction from PDF documents is considered for both rule based and machine learning based approaches. We also describe a digital library search engine that indexes figure captions and mentions from 150K documents, extracted by our custom built extractor.
ISSN:1520-5363
2379-2140
DOI:10.1109/ICDAR.2013.34