Segmentation methods for character recognition: from segmentation to document structure analysis

Author

Fujisawa, Hiromichi ; Nakano, Yasuaki ; Kurino, Kiyomichi

Author_Institution

Hitachi Ltd., Tokyo, Japan

Volume

80

Issue

7

fYear

1992

fDate

7/1/1992 12:00:00 AM

Firstpage

1079

Lastpage

1092

Abstract

A pattern-oriented segmentation method for optical character recognition that leads to document structure analysis is presented. As a first example, segmentation of handwritten numerals that touch are treated. Connected pattern components are extracted, and spatial interrelations between components are measured and grouped into meaningful character patterns. Stroke shapes are analyzed and a method of finding the touching positions that separates about 95% of connected numerals correctly is described. Ambiguities are handled by multiple hypotheses and verification by recognition. An extended form of pattern-oriented segmentation, tabular form recognition, is considered. Images of tabular forms are analyzed, and frames in the tabular structure are extracted. By identifying semantic relationships between label frames and data frames, information on the form can be properly recognized

Keywords

document image processing; optical character recognition; OCR; character patterns; character recognition; connected pattern components; data frames; document structure analysis; handwritten numerals; label frames; multiple hypotheses; segmentation; semantic relationships; spatial interrelations; tabular form recognition; touching positions; Character recognition; Image segmentation; Optical character recognition software; Paper technology; Pattern classification; Pattern recognition; Pixel; Text analysis; Usability; Writing;

fLanguage

English

Journal_Title

Proceedings of the IEEE

Publisher

ieee

ISSN

0018-9219

Type

jour

DOI

10.1109/5.156471

Filename

156471