Document Type

Article

Publication Date

2021

Publication Title

CEUR Workshop Proceedings: Proceedings of the Workshop on Scientific Document Understanding co-located with 35th AAAI Conference on Artificial Intelligence (AAAI 2021)

Volume

2831

Pages

11 (1-4)

Conference Name

Workshop on Scientific Document Understanding co-located with 35th AAAI Conference on Artificial Intelligence (AAAI 2021), February 9, 2021, Remote, Online

Abstract

Scientific documents often contain significant information in figures. The United States Patent and Trademark Office (USPTO) awards thousands of patents each week, with each patent containing on the order of a dozen figures. The information conveyed by these figures typically include a drawing or diagram, a label, caption and reference text within the document. Yet associating the short bits of text to the figure is challenging when labels are embedded within the figure, as they typically are in patents. Using patents as a testbench, this paper highlights an open challenge in analyzing all of the information presented in scientific/technical documents - namely, there is a technological gap in recognizing characters embedded in drawings, which leads to difficulties in processing the text associated with scientific figures. We demonstrate that automatically reading the figure label in patent diagram figures is an open challenge, as we evaluate several state-of-the-art optical character recognition (OCR) methods on recent patents. Because the visual characteristics of drawings/diagrams are quite similar to that of text (high contrast, width of strokes, etc), separating the diagram from the text is challenging and leads to both (a) false detection of characters from pixels that are not text and (b) missed text that is critical for identifying the figure number. We develop a method for automatically reading the patent figure labels by first identifying the bounding box containing the label using a novel non-convex hull approach, and then demonstrate the success of OCR when the text is isolated from the diagram.

Rights

© 2021 by the authors.

This paper is published under a Creative Commons Attribution 4.0 International (CC BY 4.0) License.

Bibliographic data published under a CC0 1.0 Universal Public Domain Dedication.

Original Publication Citation

Gong, M., Wei, X., Oyen, D., Wu, J., Gryder, M., & Yang, L. (2021). Recognizing figure labels in patents. CEUR Workshop Proceedings, 2831, 11. https://ceur-ws.org/Vol-2831/paper11.pdf

ORCID

0000-0003-0173-4463 (Wu)

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