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Markov Random Field Based Text Identification from Annotated Machine Printed Documents

Markov Random Field Based Text Identification from Annotated Machine Printed Documents,10.1109/ICDAR.2009.237,Xujun Peng,Srirangaraj Setlur,Venu Govin

Markov Random Field Based Text Identification from Annotated Machine Printed Documents   (Citations: 3)
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In this paper, we describe an approach to segment hand- written text, machine printed text and noise from annotated machine printed documents. Three categories of word level features are extracted. We use a modified K-Means clus- tering algorithm for classification followed by a relabeling procedure using Markov Random Field(MRF) based on a conceptofneighboringpatchesandBeliefPropagation(BP) rules. Experimental results on an imbalanceddata set show that our approach achieves an overall recall of 96.33% .
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