A Neural Approach for the Offline Recognition of the Arabic Handwritten Words of the Algerian Departments - Aix-Marseille Université Access content directly
Journal Articles International Journal of Computer, Electrical, Automation, Control and Information Engineering Year : 2015

A Neural Approach for the Offline Recognition of the Arabic Handwritten Words of the Algerian Departments

Salim Ouchtati
Mouldi Bedda
  • Function : Author

Abstract

In the context of the handwriting recognition, we propose an off line system for the recognition of the Arabic handwritten words of the Algerian departments. The study is based mainly on the evaluation of neural network performances, trained with the gradient back propagation algorithm. The used parameters to form the input vector of the neural network are extracted on the binary images of the handwritten word by several methods. The Distribution parameters, the centered moments of the different projections of the different segments, the centered moments of the word image coding according to the directions of Freeman, and the Barr features applied binary image of the word and on its different segments. The classification is achieved by a multi layers perceptron. A detailed experiment is carried and satisfactory recognition results are reported.
No file

Dates and versions

hal-01389849 , version 1 (30-10-2016)

Identifiers

  • HAL Id : hal-01389849 , version 1

Cite

Salim Ouchtati, Jean Sequeira, Mouldi Bedda. A Neural Approach for the Offline Recognition of the Arabic Handwritten Words of the Algerian Departments. International Journal of Computer, Electrical, Automation, Control and Information Engineering, 2015, 9, pp.1910-1916. ⟨hal-01389849⟩
136 View
0 Download

Share

Gmail Facebook X LinkedIn More