Warped image restoration with applications to digital libraries

Recently, high resolution digital cameras have made the digitization process more flexible and convenient than traditional scanning technology. Therefore, document image analysis techniques need to be extended to handle images captured using ordinary hand-held cameras under an uncontrolled environment. In this paper, we propose an image restoration technique that corrects various warping distortions such as rolling curl, binding curl and fold distortions in camera images of geometrically distorted documents. Our goal is to restore these arbitrarily warped document images to a planar shape so as to facilitate OCR. Our method uses spline interpolation technique based on a ruled surface model constructed from text lines in the 2D document image. Comparisons on OCR performance using Microsoft imaging software with two existing methods show an encouraging improvement in terms of recall and precision. The OCR precision on the corrected images using our method is improved up to 21.8% comparing to original images with a resolution of 3 mega pixels.