Page Curling Correction for Scanned Books Using Local Distortion Information

The correction of page curling in scanned document images has attracted a lot of attention in recent years. Fixing page curling is essential because of the resulting damage in the visual perception of the scanned text and the ensuing reduction in OCR performance on the distorted image. It has been generally concluded that correcting the distortion due to page curling will serve as a solid basis for increased OCR accuracy. We present a novel approach for the efficient correction of page curling in the images of scanned book pages. The approach is based on the fact that approximately 70% of the words in any book are recurring terms. Thus, for many distorted words, a distinct and clear reference word can be found. Our work computes a global, polynomial transformation-based correction for the page distortion. This correction is based on the estimation of various local distortions in the given page, which are characterized by located words. Experiments on the scanned page images of an 18th century book printed in Old Gothic font have demonstrated the effectiveness of the proposed technique.