Feature selection for off-line recognition of different size signatures

Author

Cavalcanti, George D da C ; Dória, Rodrigo C. ; Filho, Edson C de B C

Author_Institution

Centro de Informatica, Univ. Fed. de Pernambuco, Recife, Brazil

fYear

2002

fDate

2002

Firstpage

355

Lastpage

364

Abstract

The aim of this work is to select a set of features, which have good performance to solve the problem of signature recognition of different sizes. The signature database was formed for three sizes of signatures per user, small, median and big. This study uses structural features, pseudo-dynamic features and five moment groups. The feature selection method chosen is the one that select the best individual features based on classifiers like Bayes and k-NN.

Keywords

Bayes methods; feature extraction; handwriting recognition; Bayes classifier; different size signatures; feature selection; k-NN classifier; moment groups; off-line recognition; performance; pseudo-dynamic features; signature database; signature recognition; structural features; Cameras; Data analysis; Data mining; Feature extraction; Forgery; Handwriting recognition; Spatial databases;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks for Signal Processing, 2002. Proceedings of the 2002 12th IEEE Workshop on

Print_ISBN

0-7803-7616-1

Type

conf

DOI

10.1109/NNSP.2002.1030047

Filename

1030047

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2199609