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DOI: 10.14569/IJACSA.2018.091069
PDF

KNN and ANN-based Recognition of Handwritten Pashto Letters using Zoning Features

Author 1: Sulaiman Khan
Author 2: Hazrat Ali
Author 3: Zahid Ullah
Author 4: Nasru Minallah
Author 5: Shahid Maqsood
Author 6: Abdul Hafeez

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 9 Issue 10, 2018.

  • Abstract and Keywords
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Abstract: This paper presents an intelligent recognition sys-tem for handwritten Pashto letters. However, handwritten char-acter recognition is challenging due to the variations in shape and style. In addition to that, these characters naturally vary among individuals. The identification becomes even daunting due to the lack of standard datasets comprising of inscribed Pashto letters. In this work, we have designed a database of moderate size, which encompasses a total of 4488 images, stemming from 102 distinguishing samples for each of the 44 letters in Pashto. Furthermore, the recognition framework extracts zoning features followed by K-Nearest Neighbour (KNN) and Neural Network (NN) for classifying individual letters. Based on the evaluation, the proposed system achieves an overall classification accuracy of approximately 70.05% by using KNN, while an accuracy of 72% through NN at the cost of an increased computation time.

Keywords: KNN; deep neural network; OCR; zoning technique; Pashto; character recognition; classification

Sulaiman Khan, Hazrat Ali, Zahid Ullah, Nasru Minallah, Shahid Maqsood and Abdul Hafeez, “KNN and ANN-based Recognition of Handwritten Pashto Letters using Zoning Features” International Journal of Advanced Computer Science and Applications(IJACSA), 9(10), 2018. http://dx.doi.org/10.14569/IJACSA.2018.091069

@article{Khan2018,
title = {KNN and ANN-based Recognition of Handwritten Pashto Letters using Zoning Features},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2018.091069},
url = {http://dx.doi.org/10.14569/IJACSA.2018.091069},
year = {2018},
publisher = {The Science and Information Organization},
volume = {9},
number = {10},
author = {Sulaiman Khan and Hazrat Ali and Zahid Ullah and Nasru Minallah and Shahid Maqsood and Abdul Hafeez}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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