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Stitched Multipanel Biomedical Figure Separation.

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IEEE, 28th International Symposium on Computer-Based Medical Systems (CBMS), pp. 54-59, 2015.
Abstract: 

We present a novel technique to separate subpanels from stitched multipanel figures appearing in biomedical research articles. Since such figures may comprise images from different imaging modalities, separating them is a critical first step for effective biomedical content-based image retrieval (CBIR). The method applies local line segment detection based on the graylevel pixel changes. It then applies a line vectorization process that connects prominent broken lines along the subpanel boundaries while eliminating insignificant line segments within the subpanels. We have validated our fully automatic technique on a subset of stitched multipanel biomedical figures extracted from articles within the Open Access subset of PubMed Central repository and have achieved precision and recall of 81.22% and 85.08%, respectively.

KC S, Antani SK, Thoma GR. Stitched Multipanel Biomedical Figure Separation. IEEE, 28th International Symposium on Computer-Based Medical Systems (CBMS), pp. 54-59, 2015.