Hough-based model for recognizing bar charts in document images
YanPing Zhou, Chew Lim Tan · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2000
Bar charts are the most basic graphic representation for scientific data in technical and business papers. The objective of bar chart recognition in document image analysis is to extract graphics and text primitives structurally, then to correlate graphic interpretative information with text primitives semantically. This paper proposes a new model for generic bar chart recognition. We first change the image space into the Hough space by applying Hough Transform on the feature points. Then we use hypothesis-testing bar pattern searching algorithm to detect the bar patterns. We also apply a new text primitives grouping algorithm to extract text primitives. Finally, we interpret bar primitives by correlating them with corresponding text primitives like human's visual processing. The results show that the new model can recognize bar charts lying in any orientations, such as slant bar charts, or even hand-drawn bar charts.