DocumentCode :
311113
Title :
A syntactic business form classifier
Author :
Ting, Antoine ; Leung, Maylor K. ; Hui, Siu-Cheung ; Chan, Kai-Yun
Author_Institution :
Sch. of Appl. Sci., Nanyang Technol. Inst., Singapore
Volume :
1
fYear :
1995
fDate :
14-16 Aug 1995
Firstpage :
301
Abstract :
A classifier is proposed in this paper to extract structural information from business forms. The classifier is built upon existing techniques and takes advantage of the highly structured nature of forms, containing lines, boxes and text. Improvements are made to widen the scope of the classifier to handle some unexpected cases from real images. A syntactic representation is built from the detected features using their positions and lengths. The information recorded in this representation is independent of scale and displacement. A filled in form can then be compared to prerecorded blank forms to see which of these fits the best. Encouraging experimental results have been obtained
Keywords :
business forms; document image processing; image classification; knowledge acquisition; knowledge representation; boxes; business form classifier; classifier; experimental results; information recorded; lines; structural information; syntactic representation; text; Business; Character recognition; Computer vision; Data mining; Electronics packaging; Information retrieval; Robustness; Software systems; Spatial databases; Storage automation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Document Analysis and Recognition, 1995., Proceedings of the Third International Conference on
Conference_Location :
Montreal, Que.
Print_ISBN :
0-8186-7128-9
Type :
conf
DOI :
10.1109/ICDAR.1995.598999
Filename :
598999
Link To Document :
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