  Figures visually represent an essential piece of information and provide an
effective means to communicate scientific facts. Recently there have been many
efforts toward extracting data directly from figures, specifically from tables,
diagrams, and plots, using different Artificial Intelligence and Machine
Learning techniques. This is because removing information from figures could
lead to deeper insights into the concepts highlighted in the scientific
documents. In this survey paper, we systematically categorize figures into five
classes - tables, photos, diagrams, maps, and plots, and subsequently present a
critical review of the existing methodologies and data sets that address the
problem of figure classification. Finally, we identify the current research
gaps and provide possible directions for further research on figure
classification.
