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Title: Chart recognition and interpretation in document images
Keywords: Graphics Recognition,Chart Recognition and Interpretation,Hough Transform,Statistical Modeling,Hidden Markov Model,Zoned Directional X-Y Tree
Issue Date: 21-Sep-2004
Citation: ZHOU YANPING (2004-09-21). Chart recognition and interpretation in document images. ScholarBank@NUS Repository.
Abstract: In graphics recognition, chart recognition and interpretation is a procedure to change scientific chart images into computer readable form. In this dissertation, we have investigated four problem domains in it. First, we propose a hierarchical statisticalmodel-based framework for chart recognition system. Second, we propose an improved projection-based plot area detection method to detect plot areas and a Hough-based axis detection algorithm to detect axes. Third, we propose a new approach for chart classification and segmentation based on statistical modeling. A novel chart classification approach based on Hidden Markov Models is proposed. A new approach for chart segmentation using optimal path finding is also proposed. Fourth, we propose a novel structure called zoned directional X-Y tree to hierarchically represent the text primitives in charts. An algorithm of generating the zoned directional X-Y tree is presented. Both results from chart segmentation and text primitive analysis are correlated for chart interpretation.
Appears in Collections:Ph.D Theses (Open)

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