Hybrid Rough Neural Network Model for Signature Recognition

  • Mohamed Elhoseny
  • Amir Nabil
  • Aboul Ella Hassanien
  • Diego Oliva
Part of the Studies in Computational Intelligence book series (SCI, volume 730)


This chapter introduces an offline signature recognition technique using rough neural network and rough set. Rough neural network tries to find better recognition performance to classify the input offline signature images. Rough sets have provided an array of tools which turned out to be especially adequate for conceptualization, organization, classification, and analysis of various types of data, when dealing with inexact, uncertain, or vague knowledge. Also, rough sets discover hidden pattern and regularities in application. This new hybrid technique achieves good results, since the short rough neural network algorithm is neglected by the grid features technique, and then the advantages of both techniques are integrated.


Offline signature Recognition Neural network 


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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Mohamed Elhoseny
    • 1
    • 3
  • Amir Nabil
    • 1
  • Aboul Ella Hassanien
    • 2
    • 3
  • Diego Oliva
    • 3
    • 4
  1. 1.Faculty of Computers and InformationMansoura UniversityMansouraEgypt
  2. 2.Faculty of Computers and Information, Information Technology DepartmentCairo UniversityGizaEgypt
  3. 3.Scientific Research Group in Egypt (SRGE)CairoEgypt
  4. 4.Departamento de Ciencias ComputacionalesTecnológico de MonterreyJalMexico

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