An efficient skew estimation technique for scanned documents: an application of piece-wise painting algorithm

In this paper, an efficient skew estimation technique based on iterative employment of the Piece-wise Painting Algorithm (PPA) on document images is presented. The PPA is initially employed on the document image in both horizontal and vertical directions to obtain two horizontally and vertically painted images. A small number of horizontal (vertical) regions, called horizontal (vertical) bands, are then selected from the horizontally (vertically) painted images. Top (left), middle (middle) and bottom (right) points of the horizontal (vertical) bands are identified in 6 separate lists. A linear regression and a geometric line drawing method are applied on the selected points in each list and subsequently two fit lines are drawn. A voting approach based on statistical mode of angles obtained from the fit lines is also proposed to find the best-fit line amongst all the lines. Based on the slope of the best-fit line, the skew angle of the document image is finally estimated and the document skew is corrected. This process is iteratively applied until the estimated skew is less than 1°. The proposed technique was tested extensively on three different datasets containing various categories of document images and encouraging results were obtained.