Issue No. 04 - April (2008 vol. 30)
Jian Liang , IEEE
Daniel DeMenthon , IEEE
David Doermann , IEEE
Compared to typical scanners, handheld cameras offer convenient, flexible, portable, and non-contactimage capture, which enables many new applications and breathes new life into existing ones. However,camera-captured documents may suffer from distortions caused by non-planar document shape andperspective projection, which lead to failure of current OCR technologies. We present a geometricrectification framework for restoring the frontal-flat view of a document from a single camera-capturedimage. Our approach estimates 3D document shape from texture flow information obtained directlyfrom the image without requiring additional 3D/metric data or prior camera calibration. Our frameworkprovides a unified solution for both planar and curved documents and can be applied in many, especiallymobile, camera-based document analysis applications. Experiments show that our method producesresults that are significantly more OCR compatible than the original images.
Camera-based OCR, image rectification, shape estimation, texture flow analysis.
D. Doermann, J. Liang and D. DeMenthon, "Geometric Rectification of Camera-Captured Document Images," in IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 30, no. , pp. 591-605, 2007.