Integrated segmentation and recognition of connected handwritten characters with recurrent neural network

Author

Lee, Seong-Whan ; Lee, Eung-Jae

Author_Institution

Dept. of Comput. Sci., Korea Univ., Seoul, South Korea

Volume

1

fYear

1995

fDate

14-16 Aug 1995

Firstpage

413

Abstract

In this paper, we propose an integrated segmentation and recognition method for recognizing connected handwritten characters with recurrent neural network. It has been developed to both integrate segmentation and recognition within a single recurrent neural network and recognize connected handwritten characters using the spatial dependencies in the images of connected handwritten characters. In order to verify the performance of the proposed method, experiments with the NIST database have been carried out and the performance of the proposed method has been compared with those of the previous integrated segmentation and recognition methods

Keywords

character recognition; handwriting recognition; image recognition; recurrent neural nets; NIST database; connected handwritten characters; integrated recognition; integrated segmentation; performance; recurrent neural network; spatial dependencies; Character recognition; Computer science; Data preprocessing; Handwriting recognition; Image recognition; Image segmentation; NIST; Neural networks; Pattern recognition; Recurrent neural networks;

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.1995.599025

Filename

599025