Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
531313 | Pattern Recognition | 2009 | 7 Pages |
Abstract
We propose a method for increasing word recognition accuracies by correcting the output of a handwriting recognition system. We treat the handwriting recognizer as a black box, such that there is no access to its internals. This enables us to keep our algorithm general and independent of any particular system. We use a novel method for correcting the output based on a “phrase-based” system in contrast to traditional source-channel models. We report the accuracies of two in-house handwritten word recognizers before and after the correction. We achieve highly encouraging results for a large synthetically generated dataset. We also report results for a commercially available OCR on real data.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Vision and Pattern Recognition
Authors
Faisal Farooq, Damien Jose, Venu Govindaraju,