Skew Estimation Based on Haar-Like Features

Abstract

This paper presents a novel approach for skew estimation of scanned documents. Haar-like features are firstly proposed to construct objective function and then a modified coarse-to-fine search strategy is implemented to reduce computation. Experimental results show that our skew estimation algorithm performs well on general printed documents with different contents, languages and layouts. The accuracy of skew angle estimation is comparable with or better than state-of-the-art methods.