Infographics are often an integral component of scientific documents for
reporting qualitative or quantitative findings as they make it much simpler to
comprehend the underlying complex information. However, their interpretation
continues to be a challenge for the blind, low-vision, and other print-impaired
(BLV) individuals. In this paper, we propose ChartParser, a fully automated
pipeline that leverages deep learning, OCR, and image processing techniques to
extract all figures from a research paper, classify them into various chart
categories (bar chart, line chart, etc.) and obtain relevant information from
them, specifically bar charts (including horizontal, vertical, stacked
horizontal and stacked vertical charts) which already have several exciting
challenges. Finally, we present the retrieved content in a tabular format that
is screen-reader friendly and accessible to the BLV users. We present a
thorough evaluation of our approach by applying our pipeline to sample
real-world annotated bar charts from research papers.

本文介绍了一种利用深度学习、OCR 和图像处理技术的自动化流程 ChartParser，可以将研究论文中的图表提取出来，进行分类，提取有用信息，并以易于使用的表格格式呈现给盲人、低视力和其他印刷受限 (BLV) 的人群。我们还对该方法进行了详细的评估。