The use of Gabor features for semi-automatically generated polyon-based ground truth of historical document images
Hao Wei, Mathias Seuret, Marcus Liwicki, Rolf Ingold · Digital Scholarship in the Humanities · 2017
Historical documents usually have a complex layout, making them one of the most challenging types of documents for automatic image analysis. In the pipeline of automatic document image analysis (DIA), layout analysis is an important prerequisite for further steps including optical character recognition, script analysis, and image recognition. It aims at splitting a document image into regions of interest such as text lines, background, and decorations. To train a layout analysis system, an essential prerequisite is a set of pages with corresponding ground truth (GT), i.e. existing labels (e.g. text line and decoration) annotated by human experts. Although there exist many methods and tools in GT generation, most of them are not suitable on our specific data sets. In this article, we propose to use Gabor features to generate GT, and based on Gabor features, we developed a web-based interface called DivaDiaWI. DivaDiaWI applies automatic functions using Gabor features to generate GT of text lines. For other region types such as background and decorations, users can manually draw their GT with user-friendly operations. The evaluation shows that (1) DivaDiaWI has two advantages when bringing it into context with state-of-the-art tools, (2) the automatic functions of DivaDiaWI greatly accelerate the GT generation, and (3) DivaDiaWI obtains a high score in a system usability test.