Skew angle estimation of printed document using linear regression, wavelet transform and anisotropic diffusion

In this paper, we present a method for skew angle detection of printed documents which is based on the linear regression analysis and wavelet transform, with skew angle toleration between 0deg and 180deg. In this work, the anisotropic diffusion was introduced as a step of pre-processing in order to reinforce the difference between areas and to eliminate the noise. The linear regression formula is applied on the black pixels which belong to the text line segment of the band of horizontal details (LH) in order to estimate their skew angle, then each skew angle is represented in a histogram of angle and its peak corresponds to the document skew angle. The text line segments are obtained by the binarization of the band LH. Our method is tested on about seventy five printed and varied documents, it provides good and accurate results.