2015 · 18 citations · 11 references
ComputingComputer ScienceComputer VisionInformation RetrievalMachine LearningDeep LearningDocument AnalysisDocument Image AnalysisDocument LayoutGradient-based OptimizationImage RestorationDegraded Document AnalysisDegraded Document RecognitionDocument Degradation AnalysisDocument Layout AnalysisHistorical Document AnalysisHistorical Document RecognitionImage Deterioration
We present a novel method for adding realistic degradations to historical document images in order to generate more training data. Degradation patches are extracted from other documents and applied to the target document in the gradient domain. Working in the gradient domain has not been done for this purpose in document images analysis so far. It has the advantage to prevent color inconsistencies and allows to efficiently avoid border effects. This paper contains the detailed description of our novel method, with a focus on the mathematical aspect of the transition to and from the gradient domain. Furthermore, we perform quantitative experiments where we investigate the effects of using synthetically generated training data on historical documents with different kind of degradations.
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Patrick Pérez, Michel Gangnet, Andrew Blake · 2003 · 2.1K citations
Patrick Pérez, Michel Gangnet, Andrew Blake · ACM Transactions on Graphics · 2003 · 1.7K citations · Full text
Global and local document degradation models
Tapas Kanungo, R.M. Haralick, Ihsin T. Phillips · 2002 · 142 citations