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Compound Figure Separation Combining Edge and Band Separator Detection

  • Mario TaschwerEmail author
  • Oge Marques
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9516)

Abstract

We propose an image processing algorithm to automatically separate compound figures appearing in scientific articles. We classify compound images into two classes and apply different algorithms for detecting vertical and horizontal separators to each class: the edge-based algorithm aims at detecting visible edges between subfigures, whereas the band-based algorithm tries to detect whitespace separating subfigures (separator bands). The proposed algorithm has been evaluated on two datasets for compound figure separation (CFS) in the biomedical domain and compares well to semi-automatic or more comprehensive state-of-the-art approaches. Additional experiments investigate CFS effectiveness and classification accuracy of various classifier implementations.

Keywords

Support Vector Machine Separator Line Meta Class Horizontal Separation Compound Image 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgements

We thank Sameer Antani (NLM) and the authors of [1] for providing their compound figure separation dataset for evaluation purposes, and Laszlo Böszörmenyi (ITEC, AAU) for valuable discussions and comments on this work.

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.ITECKlagenfurt University (AAU)KlagenfurtAustria
  2. 2.Florida Atlantic University (FAU)Boca RatonUSA

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