Skew estimation for scanned documents from "noises"
Bo Yuan, C.L. Tan · 2005
The vast majority of the published skew estimation methods for scanned document images are for textual documents. These methods are based on the principle that the skew angles can be derived from the presence of the obvious text lines. The non-textual objects, such as line drawings, photographic inserts, scan artifacts including the dark bars around the borders and the center spine of bounded materials, and media contaminations are considered as "noises", thus are subject to elimination. Skew estimators that work in the presence of excessive noises are considered robust. This paper presents a skew estimation method that is based on the straight lines or edges. It uses the Muff Transform with a probe-line mapping scheme for feature identification. Various strategies for optimized line probing are devised. This method is applicable to both textual and graphical documents scanned with ordinary scanners or copiers under normal conditions. Selected images from the University of Washington English document image database I (UWDB-I) are used for its usability evaluation.