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
fDate :
29 Aug.-1 Sept. 2005
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;
Conference_Titel :
Document Analysis and Recognition, 2005. Proceedings. Eighth International Conference on
Print_ISBN :
0-7695-2420-6
DOI :
10.1109/ICDAR.2005.43
