Alternatives for Page Skew Compensation in Writer Identification

Traditionally, page images undergo pre-processing before the later stages of document analysis are applied. One common pre-processing step is to calculate and correct for the presence of simple page skew through a compensating rotation. Such operations modify the original input image, however, and in doing so may discard or obscure useful information. In this paper, we examine the impact of page deskewing on the task of writer identification for complicated handwritten documents. As an alternative to rotating the page image, we demonstrate a method that compensates for page skew during feature extraction. Experimental evaluation involving 61 Arabic writers and 610 page images show that handling page skew during feature extraction can benefit writer ID with a significant 1.4% gain in accuracy. In addition, we also obtain a 4.7% gain after improving an existing contour-based feature extraction method.