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Geometric rectification of camera-captured document images.

Research paper by Jian J Liang, Daniel D DeMenthon, David D Doermann

Indexed on: 16 Feb '08Published on: 16 Feb '08Published in: IEEE transactions on pattern analysis and machine intelligence



Abstract

Compared to typical scanners, handheld cameras offer convenient, flexible, portable, and non-contact image 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 and perspective projection, which lead to failure of current OCR technologies. We present a geometric rectification framework for restoring the frontal-flat view of a document from a single camera-captured image. Our approach estimates 3D document shape from texture flow information obtained directly from the image without requiring additional 3D/metric data or prior camera calibration. Our framework provides a unified solution for both planar and curved documents and can be applied in many, especially mobile, camera-based document analysis applications. Experiments show that our method produces results that are significantly more OCR compatible than the original images.