Compound Figure Separation at MMM 2016

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Our extended work on compound figure separation has been accepted as a regular paper at MMM 2016 conference. A preprint is available here.

Update: Slides of my presentation on Jan 5, 2016 at MMM conference. Official link to published paper. BibTeX citation:

Title                    = {Compound Figure Separation Combining Edge and Band Separator Detection},
Author                   = {Taschwer, Mario and Marques, Oge},
Booktitle                = {MultiMedia Modeling},
Publisher                = {Springer International Publishing},
Year                     = {2016},
Editor                   = {Tian, Qi and Sebe, Nicu and Qi, Guo-Jun and Huet, Benoit and Hong, Richang and Liu, Xueliang},
Pages                    = {162--173},
Series                   = {Lecture Notes in Computer Science},
Volume                   = {9516},

Doi                      = {10.1007/978-3-319-27671-7_14},
ISBN                     = {978-3-319-27670-0}

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 recent datasets for compound figure separation (CFS) in the biomedical domain and achieves a slightly better detection accuracy than state-of-the-art approaches. Conducted experiments investigate CFS effectiveness and classification accuracy of various classifier implementations.