Title:	AN EFFICIENT DOCUMENT IMAGE RECONSTRUCTION AND BINARIZATION METHOD USING COMPRESSED SENSING
Author(s):	J V Satyanarayana , A G Ramakrishnan
ISBN:	978-972-8924-84-3
Editors:	Yingcai Xiao, Tomaz Amon and Piet Kommers
Year:	2009
Edition:	Single
Keywords:	Document binarization, Compressed sensing
Type:	Short Paper
First Page:	287
Last Page:	291
Language:	English
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Paper Abstract:	In this paper, we present a novel approach of document image acquisition with reduced number of measurements, requiring lesser number of sensing elements. Reduction in the number of sensors also directly implies faster acquisition. Our approach is built around the Compressed Sensing paradigm, in which signals which are sparse can be captured and reconstructed with considerably lesser number of measurements than required by Nyquist sensing. Signal reconstruction algorithms used in Compressed Sensing are computationally intensive. A brief survey of some of the popular reconstruction algorithms is also given in the paper. In the algorithm proposed in this work, the reconstruction step associated with recovering the binary image from the Compressed Sensing measurements is pruned to take advantage of the inherent requirement of the binarization of the acquired image. Binarization of captured documents which is an essential step for post processing is built into the proposed scheme.
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