Multi-Digit Handwritten Sindhi Numerals Recognition using SOM Neural Network - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue Mehran University Research Journal of Engineering and Technology Année : 2017

Multi-Digit Handwritten Sindhi Numerals Recognition using SOM Neural Network

Résumé

In this research paper a multi-digit Sindhi handwritten numerals recognition system using SOM Neural Network is presented. Handwritten digits recognition is one of the challenging tasks and a lot of research is being carried out since many years. A remarkable work has been done for recognition of isolated handwritten characters as well as digits in many languages like English, Arabic, Devanagari, Chinese, Urdu and Pashto. However, the literature reviewed does not show any remarkable work done for Sindhi numerals recognition. The recognition of Sindhi digits is a difficult task due to the various writing styles and different font sizes. Therefore, SOM (Self-Organizing Map), a NN (Neural Network) method is used which can recognize digits with various writing styles and different font sizes. Only one sample is required to train the network for each pair of multi-digit numerals. A database consisting of 4000 samples of multi-digits consisting only two digits from 10-50 and other matching numerals have been collected by 50 users and the experimental results of proposed method show that an accuracy of 86.89% is achieved.
Fichier principal
Vignette du fichier
Chapter-14 (Asghar Chandio-Mahwish Laghari-Akhtar Jalbani).pdf (171.3 Ko) Télécharger le fichier
Origine : Fichiers éditeurs autorisés sur une archive ouverte
Loading...

Dates et versions

hal-01700634 , version 1 (05-02-2018)

Licence

Paternité

Identifiants

  • HAL Id : hal-01700634 , version 1

Citer

Asghar Ali Chandio, Akhtar Hussain Jalbani, Mehwish Leghari, Ashfaque Ahmed Awan. Multi-Digit Handwritten Sindhi Numerals Recognition using SOM Neural Network. Mehran University Research Journal of Engineering and Technology, 2017, 36 (4), pp.901-908. ⟨hal-01700634⟩
53 Consultations
194 Téléchargements

Partager

Gmail Facebook X LinkedIn More