Robust Cell Extraction Method for Form Documents Based on Intersection Searching and Global Optimization

This paper presents a method to extract cells from form documents of an unknown format based on intersection tracking and global optimization. Because of the increasing varieties of forms and complications in the forms, cell extraction has become a key factor in automatic form recognition. The proposed method produces cell candidates by using intersection features and tracing intersection points to form closed regions. Then, global optimization is carried out to determine a set of cells having the highest likelihood. Maintaining precision for 82 kinds of forms, the proposed method achieved a recall rate of 80.4% whereas the conventional method achieved a recall rate of 77.1%.