Affiliations: Departamento de Ingeniería de Sistemas y
Automática, Universidad Politécnica de Cartagena, Campus de la Muralla del
Mar, s/n, 30202, Cartagena, Murcia, Spain. Tel.: +34 68 325477; Fax: +34 68
325355; E-mail: Miguel.Pinzolas@upct.es | Departamento de Matemática e Informática,
Universidad Pública de Navarra. Campus de Arrosadía, s/n, 31006,
Pamplona, Navarra, Spain. Tel.: +34 48 169532; Fax: +34 48 169521; E-mail:
josej.astrain@unavarra.es | Departamento de Automática y Computación,
Universidad Pública de Navarra. Campus de Arrosadía, s/n, 31006, Pamplona,
Navarra, Spain. Tel.: +34 48 169645; Fax: +34 48 168924; E-mail:
jesusv@unavarra.es
Note: [] Corresponding author
Abstract: A neuro-fuzzy system for isolated hand-written digit recognition
using a similarity fuzzy measure is presented. The system is composed of two
main blocks: a first block that normalises the input and compares it with a set
of fuzzy patterns, and a second block with a multilayer perceptron (MLP) to
perform the definitive classification. The comparison with the fuzzy patterns
is carried out via a fuzzy similarity measure that uses the Yager parametric
norms and co-norms. Along this work, several values of the parameter have been
studied, in order to obtain the optimum. The simplicity of the method makes it
extremely quick. Recognition accuracy of the method is about 90% single
classification, and close to 97,5% classification scheme.
