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Paper details
Number 3 - September 2020
Volume 30 - 2020
Line segmentation of handwritten text using histograms and tensor voting
Tomasz Babczyński, Roman Ptak
Abstract
There are a large number of historical documents in libraries and other archives throughout the world. Most of them are
written by hand. In many cases they exist in only one specimen and are hard to reach. Digitization of such artifacts can
make them available to the community. But even digitized, they remain unsearchable, and an important task is to draw the
contents in the computer readable form. One of the first steps in this direction is to recognize where the lines of the text are.
Computational intelligence algorithms can be used to solve this problem. In the present paper, two groups of algorithms,
namely, projection-based and tensor voting-based, are compared. The performance is evaluated on a data set and with the
procedure proposed by the organizers of the ICDAR 2009 competition.
Keywords
document image processing, handwritten text line segmentation, projection profile, text string, off-line cursive script recognition, ICDAR 2009 competition