Automatic Table Ground Truth Generation and a Background-Analysis-based Table Structure Extraction Method

We first describe an automatic table ground truth generation system which can efficiently generate a large amount of accurate table ground truth suitable for the development of table detection algorithms. Then a novel background analysis-based, coarse-to-fine table identification algorithm and an X-Y cut table decomposition algorithm are described. We discuss an experimental protocol to evaluate the table detection algorithms. For a total of 1,125 document pages having 518 table entities and a total of 10,941 cell entities, our table detection algorithm takes line, word segmentation results as input and obtains around 90% cell correct detection rates.