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

Geometric Rectification of Creased Document Images based on Isometric Mapping