ChartParser: Automatic Chart Parsing for Print-Impaired
This addresses accessibility for print-impaired users by automating chart interpretation, though it is incremental as it focuses on bar charts and builds on existing techniques.
The authors tackled the challenge of making infographics accessible to blind, low-vision, and print-impaired individuals by developing ChartParser, an automated pipeline that extracts, classifies, and retrieves information from bar charts in research papers, presenting it in a screen-reader friendly tabular format, with evaluation on real-world annotated bar charts.
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.