2021 IEEE International Conference on Image Processing

19-22 September 2021 • Anchorage, Alaska, USA

Imaging Without Borders

2021 IEEE International Conference on Image Processing

19-22 September 2021 • Anchorage, Alaska, USA

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Paper Detail

Paper IDMLR-APPL-IVASR-4.5
Paper Title A TWO-STAGE FRAMEWORK FOR COMPOUND FIGURE SEPARATION
Authors Weixin Jiang, Northwestern University, United States; Eric Schwenker, Trevor Spreadbury, Nicola Ferrier, Maria Chan, Argonne National Laboratory, United States; Oliver Cossairt, Northwestern University, United States
SessionMLR-APPL-IVASR-4: Machine learning for image and video analysis, synthesis, and retrieval 4
LocationArea B
Session Time:Tuesday, 21 September, 13:30 - 15:00
Presentation Time:Tuesday, 21 September, 13:30 - 15:00
Presentation Poster
Topic Applications of Machine Learning: Machine learning for image & video analysis, synthesis, and retrieval
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Abstract Scientific literature contains large volumes of complex, unstructured figures that are compound in nature (i.e. composed of multiple images, graphs, and drawings). Separation of these compound figures is critical for information retrieval from these figures. In this paper, we propose a new strategy for compound figure separation, which decomposes the compound figures into constituent subfigures while preserving the association between the subfigures and their respective caption components. We propose a two-stage framework to address the proposed compound figure separation problem. In the first stage, the subfigure label detection module detects all subfigure labels. Then, in the subfigure detection module, the detected subfigure labels help to detect the subfigures by optimizing the feature selection process and providing the global layout information as extra features. Extensive experiments are conducted to validate the effectiveness and superiority of the proposed framework, which improves the precision by 9% compared to the benchmark.