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PUBMED FOR HANDHELDS

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  • Title: Geometric rectification of camera-captured document images.
    Author: Liang J, DeMenthon D, Doermann D.
    Journal: IEEE Trans Pattern Anal Mach Intell; 2008 Apr; 30(4):591-605. PubMed ID: 18276966.
    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.
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