Segmentation Methods for Character Recognition
Hiromichi Fujisawa, Yasuaki Nakano and Kiyomichi Kurino
Proceedings of the IEEE, Vol.80 [7], pp.1079-1092 (1992)
Abstract
This paper discusses character segmentation methods, a key technology for
character recognition that determines the usability and applicability of optical
character readers. A pattern-oriented segmentation method that leads to document
structure analysis is presented. A first example of advanced character
segmentation is touching handwritten numeral segmentation. Connected pattern
components are extracted instead of a pixel image, and spatial interrelations
between components are measured to group them into meaningful character
patterns. Stroke shapes are analyzed in the case of touching characters. A
method of finding the touching positions can separate about 95% of connected
numerals correctly. Ambiguities are handled by multiple hypotheses and
verification by recognition. An extended form of pattern-oriented segmentation
is also discussed by presenting another example of tabular form recognition.
Document images of tabular forms are analyzed, and frames in the tabular
structure can be extracted. By identifying semantic relationships between label
frames and data frames, information on the form can be properly recognized.
Advance character segmentation with a document structure analysis capability is
becoming increasingly significant in automating information extraction from
various kinds of documents.
[Segmentation of Touching Characters]
[Research Themes of Prof. Nakano.]
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First Written Before June 17, 1998
Transplanted to KSU Before June 19, 2003
Transplanted to So-net April 22, 2007
Last Update April 22, 2007
© Yasuaki Nakano 1998-2007