Abstract: The scale invariance characteristics play an essential role in pattern recognition applications, for example in computer vision, OCR (Optical Character Recognition), electronic publication, etc. In this paper, the shape based feature extraction techniques are used in terms of invariant properties and the region based FD (Fourier Descriptors) have been used for the recognition of isolated printed Sindhi characters. There are 56 isolated characters in Sindhi language than can be categorized to 20 different classes considering the shape of the base of each character. In this work, the dataset contains 4704 images of isolated printed Sindhi characters. The simulation result shows that the proposed method is a capable discriminating algorithm of Similar Sindhi characters and can easily extract the scale invariant features.

Nasreen Nizamani, Mujtaba Shaikh, Jawed Unar, Ehsan Ali, Ghulam Mustafa Bhutto and Abdul Rafay, “Optical Recognition of Isolated Machine Printed Sindhi Characters using Fourier Descriptors” International Journal of Advanced Computer Science and Applications(IJACSA), 10(6), 2019. http://dx.doi.org/10.14569/IJACSA.2019.0100635

@article{Nizamani2019,
title = {Optical Recognition of Isolated Machine Printed Sindhi Characters using Fourier Descriptors},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2019.0100635},
url = {http://dx.doi.org/10.14569/IJACSA.2019.0100635},
year = {2019},
publisher = {The Science and Information Organization},
volume = {10},
number = {6},
author = {Nasreen Nizamani and Mujtaba Shaikh and Jawed Unar and Ehsan Ali and Ghulam Mustafa Bhutto and Abdul Rafay}
}