The Impact of Ruling Lines on Writer Identification

Abstract

Paper often includes pre-printed ruling lines to help people write more neatly. This particular example of real- world noise can have a serious impact on applications such as handwriting recognition and writer identification, however. In this work, we investigate the effects of ruling lines on writer ID. We study a method for detecting and removing ruling lines and test its utility for Arabic writer identification through a series of experiments. Our preliminary results show that under realistic assumptions where ruling lines are expected to have different properties across the collection, e.g., thickness, spacing, etc., removing them significantly improves identification performance. We conclude with a discussion of work-in-progress to examine follow up questions raised by our initial investigations.