Low quality string recognition for factory automation

Author

Sawa, Kazuhiro ; Tsuruoka, Shinji ; Wakabayashi, Tetsushi ; Kimura, Funlitaka ; Miyake, Yasuji

Author_Institution

Dept. of Inf. Eng., Mie Univ., Tsu, Japan

Volume

2

fYear

1997

fDate

18-20 Aug 1997

Firstpage

475

Abstract

Describes a method for dot-printed character string recognition on a piece of steel for factory automation. Our scanned string consists of alphanumerics and the `-´ character, and the number of characters is variable from 6 to 12 characters. We propose a new recognition procedure for low-quality strings. The procedure includes image emphasis with a Gaussian Laplacian filter, the extraction of the string subimage, segmentation-recognition with dynamic programming, and fine character recognition. We evaluated its accuracy on a UNIX workstation for 1036 images (8806 characters) scanned by a monochrome video camera in the actual production line at a steel-producing factory, and the average recognition rates were 99.2% for the character recognition and 91.6% for the string recognition

Keywords

dynamic programming; factory automation; image segmentation; optical character recognition; steel industry; Gaussian Laplacian filter; UNIX workstation; accuracy evaluation; alphanumeric characters; dot-printed character strings; dynamic programming; factory automation; fine character recognition; image emphasis; image segmentation; low-quality character string recognition; monochrome video camera; production line; recognition rates; steel-producing factory; string subimage extraction; Cameras; Character recognition; Dynamic programming; Filters; Image recognition; Image segmentation; Laplace equations; Manufacturing automation; Steel; Workstations;

fLanguage

English

Publisher

ieee

Conference_Titel

Document Analysis and Recognition, 1997., Proceedings of the Fourth International Conference on

Conference_Location

Ulm

Print_ISBN

0-8186-7898-4

Type

conf

DOI

10.1109/ICDAR.1997.620543

Filename

620543