DocumentCode
3022179
Title
Adaptive OCR with limited user feedback
Author
Ma, Huanfeng ; Doermann, David
Author_Institution
Inst. of Adv. Comput. Studies, Marylang Univ., College Park, MD, USA
fYear
2005
fDate
29 Aug.-1 Sept. 2005
Firstpage
814
Abstract
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.
Keywords
document image processing; feature extraction; feedback; image classification; optical character recognition; OCR classifier; adaptive OCR; character template extraction; noisy printed document processing; optical character recognition; scanned document; user feedback; Adaptive systems; Data mining; Educational institutions; Flowcharts; Ground support; Image segmentation; Laboratories; Optical character recognition software; Optical feedback; Text analysis;
fLanguage
English
Publisher
ieee
Conference_Titel
Document Analysis and Recognition, 2005. Proceedings. Eighth International Conference on
ISSN
1520-5263
Print_ISBN
0-7695-2420-6
Type
conf
DOI
10.1109/ICDAR.2005.43
Filename
1575658
Link To Document