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		<datafield tag="980" ind1=" " ind2=" ">
			<subfield code="a">REPORT</subfield>
		</datafield>
		<datafield tag="970" ind1=" " ind2=" ">
			<subfield code="a">chen-0218/IDIAP</subfield>
		</datafield>
		<datafield tag="245" ind1=" " ind2=" ">
			<subfield code="a">Video Text Recognition Based on Markov Random Field and Grayscale Consistency Constraint</subfield>
		</datafield>
		<datafield tag="700" ind1=" " ind2=" ">
			<subfield code="a">Odobez, Jean-Marc</subfield>
		</datafield>
		<datafield tag="700" ind1=" " ind2=" ">
			<subfield code="a">Chen, Datong</subfield>
		</datafield>
		<datafield tag="856" ind1="4" ind2="0">
			<subfield code="i">EXTERNAL</subfield>
			<subfield code="u">http://publications.idiap.ch/attachments/reports/2002/rr-02-18.pdf</subfield>
			<subfield code="x">PUBLIC</subfield>
		</datafield>
		<datafield tag="088" ind1=" " ind2=" ">
			<subfield code="a">Idiap-RR-18-2002</subfield>
		</datafield>
		<datafield tag="260" ind1=" " ind2=" ">
			<subfield code="c">2002</subfield>
			<subfield code="b">IDIAP</subfield>
		</datafield>
		<datafield tag="771" ind1="2" ind2=" ">
			<subfield code="d">April 2002</subfield>
		</datafield>
		<datafield tag="500" ind1=" " ind2=" ">
			<subfield code="a">Published in Proceedings of the Int. Conf. Image Processing 2002</subfield>
		</datafield>
		<datafield tag="520" ind1=" " ind2=" ">
			<subfield code="a">A method for segmenting and recognizing text embedded in video and images is proposed in this paper. In the method, multiple segmentation hypotheses of text image are first generated based on a MRF model. Background regions in each hypothesis are then removed by using grayscale consistency constraint (GCC) in a connected component analysis procudure before being processed by an optical character recognition (OCR) software.</subfield>
		</datafield>
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