  Geometric rectification of images of distorted documents finds wide
applications in document digitization and Optical Character Recognition (OCR).
Although smoothly curved deformations have been widely investigated by many
works, the most challenging distortions, e.g. complex creases and large
foldings, have not been studied in particular. The performance of existing
approaches, when applied to largely creased or folded documents, is far from
satisfying, leaving substantial room for improvement. To tackle this task,
knowledge about document rectification should be incorporated into the
computation, among which the developability of 3D document models and
particular textural features in the images, such as straight lines, are the
most essential ones. For this purpose, we propose a general framework of
document image rectification in which a computational isometric mapping model
is utilized for expressing a 3D document model and its flattening in the plane.
Based on this framework, both model developability and textural features are
considered in the computation. The experiments and comparisons to the
state-of-the-art approaches demonstrated the effectiveness and outstanding
performance of the proposed method. Our method is also flexible in that the
rectification results can be enhanced by any other methods that extract
high-quality feature lines in the images.
