Chris Dance
Dance, C. R., "Perpective Estimation for Document Images", in Proceedings SPIE
Document Recognition IX, San Jose,20-25 January, 2002, SPIE.
There has been increasing interest in document capture with digital cameras,
since they are often more convenient to use than conventional devices such as
flatbed scanners. Unlike flatbed scanners, cameras can acquire document images
with arbitrary perspectives. Without correction, perspective distortions are
unappealing to human readers. They also make subsequent image analysis slower,
more complicated and less reliable.

The novel contribution of this paper is to view perspective estimation as a
generalisation of the well-studied skew estimation problem. Rather than
estimating one angle of rotation we must determine four angles describing the
perspective. In our method, separate estimates are made for angles describing
lines that are parallel and perpendicular to text lines. Each of these
estimates is based on a twice-iterated projection profile computation.
We give a probabilistic argument for the method and describe an efficient
implementation. Our results illustrate its primary benefits: it is robust and
accurate. The method is efficient compared with the time required to warp the
image to correct for perspective.
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