A fast algorithm for computing longest common subsequences
Communications of the ACM
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 4
A Methodology for Special Symbol Recognitions
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 4
Training on Severely Degraded Text-Line Images
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 1
Decoder Banks: Versatility, Automation, and High Accuracy without Supervised Training
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 2 - Volume 02
Improving optical character recognition through efficient multiple system alignment
Proceedings of the 9th ACM/IEEE-CS joint conference on Digital libraries
DAS '10 Proceedings of the 9th IAPR International Workshop on Document Analysis Systems
Hi-index | 0.00 |
A methodology is proposed for processing noisy printed documents with limited user feedback. Without the support of ground truth, a specific collection of scanned documents can be processed to extract character templates. The adaptiveness of this approach lies in that the extracted templates are used to train an OCR classifier quickly and with limited user feedback. Experimental results show that this approach is extremely useful for the processing of noisy documents with many touching characters.