Automatic Extraction of Data from 2-D Plots in Documents
Xiaofei Lu, James Z. Wang, Prasenjit Mitra, Clyde Lee Giles · Proceedings of the International Conference on Document Analysis and Recognition · 2007
Two-dimensional (2-D) plots in digital documents contain important information. Often, the results of scientific experiments and performance of businesses are summarized using plots. Although 2-D plots are easily understood by human users, current search engines rarely utilize the information contained in the plots to enhance the results returned in response to queries posed by end- users. We propose an automated algorithm for extracting information from line curves in 2-D plots. The extracted information can be stored in a database and indexed to answer end-user queries and enhance search results. We have collected 2-D plot images from a variety of resources and tested our extraction algorithms. Experimental evaluation has demonstrated that our method can produce results suitable for real world use.