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		<identifier>oai:zbc.uz.zgora.pl:86158</identifier>
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<dc:title xml:lang="pl"><![CDATA[Line segmentation of handwritten text using histograms and tensor voting]]></dc:title>
<dc:creator><![CDATA[Babczyński, Tomasz]]></dc:creator>
<dc:creator><![CDATA[Ptak, Roman]]></dc:creator>
<dc:subject xml:lang="pl"><![CDATA[document image processing]]></dc:subject>
<dc:subject xml:lang="pl"><![CDATA[handwritten text line segmentation]]></dc:subject>
<dc:subject xml:lang="pl"><![CDATA[projection profile]]></dc:subject>
<dc:subject xml:lang="pl"><![CDATA[text string]]></dc:subject>
<dc:subject xml:lang="pl"><![CDATA[off-line cursive script recognition]]></dc:subject>
<dc:subject xml:lang="pl"><![CDATA[ICDAR 2009 competition]]></dc:subject>
<dc:description xml:lang="pl"><![CDATA[There are a large number of historical documents in libraries and other archives throughout the world.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.]]></dc:description>
<dc:description xml:lang="pl"><![CDATA[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.]]></dc:description>
<dc:publisher><![CDATA[Zielona Góra: Uniwersytet Zielonogórski]]></dc:publisher>
<dc:contributor><![CDATA[Kołodziej, Joanna - ed.]]></dc:contributor>
<dc:contributor><![CDATA[Pllana, Sabri - ed.]]></dc:contributor>
<dc:contributor><![CDATA[Vitabile , Salvatore - ed.]]></dc:contributor>
<dc:date><![CDATA[2020]]></dc:date>
<dc:type xml:lang="pl"><![CDATA[artykuł]]></dc:type>
<dc:identifier><![CDATA[http://www.zbc.uz.zgora.pl/repozytorium/Content/86158/AMCS_2020_30_3_14.pdf]]></dc:identifier>
<dc:identifier><![CDATA[https://zbc.uz.zgora.pl/repozytorium/dlibra/publication/101250/edition/86158/content]]></dc:identifier>
<dc:identifier><![CDATA[oai:zbc.uz.zgora.pl:86158]]></dc:identifier>
<dc:source xml:lang="pl"><![CDATA[AMCS, volume 30, number 3 (2020)]]></dc:source>
<dc:source xml:lang="pl"><![CDATA[https://www.amcs.uz.zgora.pl/?action=papers&issue=117]]></dc:source>
<dc:language><![CDATA[eng]]></dc:language>
<dc:relation><![CDATA[oai:zbc.uz.zgora.pl:publication:101250]]></dc:relation>
<dc:rights xml:lang="pl"><![CDATA[Biblioteka Uniwersytetu Zielonogórskiego]]></dc:rights>
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