Geometric Rectification of Camera-captured Document Images

Geometric Rectification of Camera-captured Document Images (2007)

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by Jian Liang , Daniel Dementhon , David Doermann , Daniel Dementhon , David Doermann , College Park , Md Usa

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@MISC{Liang07geometricrectification,
    author = {Jian Liang and Daniel Dementhon and David Doermann and Daniel Dementhon and David Doermann and College Park and Md Usa},
    title = {Geometric Rectification of Camera-captured Document Images},
    year = {2007}
}

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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. Index Terms Camera-based OCR, image rectification, shape estimation, texture flow analysis.

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