An iterative graph cut optimization algorithm for a double MRF prior

Christian Wolf (1)

1 imagine - Extraction de Caractéristiques et Identification

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.

Mots clés: Document Image Restoration; Markov Random Fields; Bayesian estimation; Graph cuts; Document Image Restoration.

Domaines: Vision par ordinateur et reconnaissance de formes [cs.CV]

Christian Wolf. An iterative graph cut optimization algorithm for a double MRF prior. 2008. ⟨hal-00422548⟩