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Please use this identifier to cite or link to this item: http://dspace.library.iitb.ac.in/jspui/handle/10054/92

Title: Robust detection of skew in document images
Authors: CHAUDHURI, SUBHASIS
CHAUDHURI, AVANINDRA
Keywords: monte carlo methods
optical correlation
algorithms
linguistics
Issue Date: 1997
Publisher: IEEE
Citation: IEEE Transactions on Image Processing 6(2), 344-49
Abstract: We describe a robust yet fast algorithm for skew detection in binary document images. The method is based on interline cross-correlation in the scanned image. Instead of finding the correlation for the entire image, it is calculated over small regions selected randomly. The proposed method does not require prior segmentation of the document into text and graphics regions. The maximum median of cross-correlation is used as the criterion to obtain the skew, and a Monte Carlo sampling technique is chosen to determine the number of regions over which the correlations have to be calculated. Experimental results on detecting skews in various types of documents containing different linguistic scripts are presented here.
URI: http://dx.doi.org/10.1109/83.551708
http://hdl.handle.net/10054/92
http://dspace.library.iitb.ac.in/xmlui/handle/10054/92
ISSN: 1057-7149
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