K-Nearest Neighbor for Recognize Handwritten Arabic Character

  • Muhammad Athoillah Universitas PGRI Adi Buana Surabaya
Keywords: Arabic Character, Classification, Handwritten, Nearest Neighbor, Text Recognition

Abstract

Handwritten text recognition is the ability of a system to recognize human handwritten and convert it into digital text. Handwritten text recognition is a form of classification problem, so a classification algorithm such as Nearest Neighbor (NN) is needed to solve it. NN algorithms is a simple algorithm yet provide a good result. In contrast with other algorithms that usually determined by some hypothesis class, NN Algorithm finds out a label on any test point without searching for a predictor within some predefined class of functions. Arabic is one of the most important languages in the world. Recognizing Arabic character is very interesting research, not only it is a primary language that used in Islam but also because the number of this research is still far behind the number of recognizing handwritten Latin or Chinese research. Due to that's the background, this framework built a system to recognize handwritten Arabic Character from an image dataset using the NN algorithm. The result showed that the proposed method could recognize the characters very well confirmed by its average of precision, recall and accuracy.

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CROSSMARK
Published
2019-10-27
DIMENSIONS
How to Cite
AthoillahM. (2019). K-Nearest Neighbor for Recognize Handwritten Arabic Character. Jurnal Matematika MANTIK, 5(2), 83-89. https://doi.org/10.15642/mantik.2019.5.2.83-89