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Proceedings Paper

Segmentation of scanned document images for efficient compression
Author(s): Hei Tao Fung; Kevin J. Parker
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Paper Abstract

A scanned, complex document image may be composed of text, graphics, halftones, and pictures, whose layout is unknown. In this paper, we propose a novel segmentation scheme for scanned document images that facilitates their efficient compression. Our scheme segments an input image into binarizable components and no-binarizable components. By a binarizable component we mean that the region can be represented by no more than two gray levels (or colors) with acceptable perceptual quality. A non-binarizable component is defined as region that has to be represented by more than two gray levels (or colors) with acceptable perceptual quality. Once the components are identified, the binarizable components can be thresholded and compressed as a binary image using an efficient binary encoding scheme together with the gray values represented by the black and white pixels of the binary image. The non-binarizable components can be compressed using another suitable encoding scheme.

Paper Details

Date Published: 27 February 1996
PDF: 12 pages
Proc. SPIE 2727, Visual Communications and Image Processing '96, (27 February 1996); doi: 10.1117/12.233285
Show Author Affiliations
Hei Tao Fung, Univ. of Rochester (United States)
Kevin J. Parker, Univ. of Rochester (United States)

Published in SPIE Proceedings Vol. 2727:
Visual Communications and Image Processing '96
Rashid Ansari; Mark J. T. Smith, Editor(s)

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