OCR Error Correction Using Character Correction and Feature-Based Word Classification

04/21/2016

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by   Ido Kissos, et al.

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This paper explores the use of a learned classifier for post-OCR text correction. Experiments with the Arabic language show that this approach, which integrates a weighted confusion matrix and a shallow language model, improves the vast majority of segmentation and recognition errors, the most frequent types of error on our dataset.