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Review of chart image detection and classification

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Abstract

This paper presents a complete review of different approaches across all components of the chart image detection and classification up to date. A set of 89 scientific papers is collected, analyzed, and enlisted into four categories: chart-type classification, chart text processing, chart data extraction, and chart description generation. Detailed information about problem formulation and a research field is provided, and an overview of used methods in each category. Each paper's contribution is noted, including the essential information for authors in this research field. In the end, a comparison is made between the reported results. The state-of-the-art methods in each category are described, and a research direction is given. We have also analyzed the open challenges that still exist and require the author's attention.

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  1. University of Zagreb, University Computing Centre, 10000, Zagreb, Croatia

    Filip Bajić

  2. Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, 31000, Osijek, Croatia

    Josip Job

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Bajić, F., Job, J. Review of chart image detection and classification. IJDAR 26, 453–474 (2023). https://doi.org/10.1007/s10032-022-00424-5

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