Skew Estimation Based on Haar-Like Features


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.

Advances on Digital Television and Wireless Multimedia Communications
Li Song
Li Song
Professor, IEEE Senior Member

Professor, Doctoral Supervisor, the Deputy Director of the Institute of Image Communication and Network Engineering of Shanghai Jiao Tong University, the Double-Appointed Professor of the Institute of Artificial Intelligence and the Collaborative Innovation Center of Future Media Network, the Deputy Secretary-General of the China Video User Experience Alliance and head of the standards group.