An iterative graph cut optimization algorithm for a double MRF prior
Résumé
In a previous publication we presented a double MRF model capable of separatly regularizing the recto and verso side of a document suffering from ink bleed through. In this paper we show that this model naturally leads to an efficient optimization method based on the minimum cut/maximum flow in a graph. The proposed method is evaluated on scanned document images from the 18th century, showing an improvement of character recognition results compared to other restoration methods.
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