Multi-Digit Handwritten Sindhi Numerals Recognition using SOM Neural Network

Asghar Ali Chandio; Akhtar Hussian Jalbani; Mehwish Laghari; Shafique Ahmed Awan

doi:10.22581/muet1982.1704.14

Asghar Ali Chandio Department of Information Technology, Quaid-e-Awam University of Engineering, Science & Technology, Nawabshah.
Akhtar Hussian Jalbani Department of Information Technology, Quaid-e-Awam University of Engineering, Science and Technology, Nawabshah
Mehwish Laghari Department of Information Technology, Quaid-e-Awam University of Engineering, Science and Technology, Nawabshah
Shafique Ahmed Awan Department of Computer Science and Information Technology, Benazir Bhutto Shaheed University, Lyari, Karachi

DOI: https://doi.org/10.22581/muet1982.1704.14

Abstract

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.