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CVPR
2005
IEEE

Restoration and Recognition in a Loop

14 years 5 months ago
Restoration and Recognition in a Loop
In this paper we present a novel learning based method for restoring and recognizing images of digits that have been blurred using an unknown kernel. The novelty of our work is an iterative loop that alternates between recognition and restoration stages. In the restoration stage we model the image as an undirected graphical model over the image patches with the compatibility functions represented as nonparametric kernel densities. Compatibility functions are initially learned using uniform random samples from the training data. We solve the inference problem by an extended version of the non-parametric belief propagation algorithm in which we introduce the notion of partial messages. We close the loop by using the confidence scores of the recognition to non-uniformly sample from the training set in order to retrain the compatibility functions. We show experimental results on synthetic and license plate images.
Mithun Das Gupta, ShyamSundar Rajaram, Nemanja Pet
Added 12 Oct 2009
Updated 29 Oct 2009
Type Conference
Year 2005
Where CVPR
Authors Mithun Das Gupta, ShyamSundar Rajaram, Nemanja Petrovic, Thomas S. Huang
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