A statistical learning approach to document image analysis

In the field of computer analysis of document images, the problems of physical and logical layout analysis have been approached through a variety of heuristic, rule-based, and grammar-based techniques. In this paper we investigate the effectiveness of statistical pattern recognition algorithms for solving these two problems, and report results suggesting that these more complex and powerful techniques are worth pursuing. First, we developed a new software environment for manual page image segmentation and labeling, and used it to create a dataset containing 932 page images from academic journals. Next, a physical layout analysis algorithm based on a logistic regression classifier was developed, and found to outperform existing algorithms of comparable complexity. Finally, three statistical classifiers were applied to the logical layout analysis problem, also with encouraging results.