Character recognition by geometrical moments on structural decompositions

Author

Foggia, P. ; Sansone, C. ; Tortorella, F. ; Vento, M.

Author_Institution

Dipt. di Inf. e Sistemistica, Univ. degli Studi di Napoli Federico II, Italy

Volume

1

fYear

1997

fDate

18-20 Aug 1997

Firstpage

6

Abstract

A novel description method is presented. It is based on the combination of structural and statistical approaches, and is applied to the problem of unconstrained isolated handwritten character recognition. Characters are preliminarily decomposed in terms of structural primitives (circular arcs) and successively described in terms of statistical features (geometrical moments suitably normalized). A multilayer perceptron is adopted in the classification stage. Results of the method on the digits of the ETL Database are reported

Keywords

computational geometry; handwriting recognition; multilayer perceptrons; pattern classification; statistical analysis; ETL Database; circular arcs; classification stage; description method; geometrical moments; multilayer perceptron; statistical approach; statistical features; structural decompositions; structural primitives; unconstrained isolated handwritten character recognition; Algorithm design and analysis; Character recognition; Data mining; Data structures; Decision theory; Extraterrestrial measurements; Multilayer perceptrons; Pattern recognition; Performance evaluation; Spatial databases;

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.1997.619804

Filename

619804