An Accurate Handwritten Digits Recognition system Based on DWT and FCT

Authors

Mustafa S. Kadhm Imam Ja'afar Al-sadiq University, Department of Computer Techniques Engineering, Baghdad, Iraq.
Duaa Enteesha Mhawi Computer Science, Central Technical University, Technical Management Institute, Baghdad, Iraq.
Rana Mohammed H. Zaki Computer Science Department, University of Technology, Baghdad, Iraq.

DOI:

https://doi.org/10.24996/ijs.2017.58.4B.23

Keywords:

Handwritten digit, DWT, FCT, KNN, FCM

Abstract

In this paper an accurate Indian handwritten digits recognition system is
proposed. The system used three proposed method for extracting the most effecting
features to represent the characteristic of each digit. Discrete Wavelet Transform
(DWT) at level one and Fast Cosine Transform (FCT) is used for features extraction
from the thinned image. Besides that, the system used a standard database which is
ADBase database for evaluation. The extracted features were classified with KNearest
Neighbor (KNN) classifier based on cityblock distance function and the
experimental results show that the proposed system achieved 98.2% recognition
rate.

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Published

2021-11-29

Issue

Vol 58 No 4B (2017)

Section

Mathematics

How to Cite

An Accurate Handwritten Digits Recognition system Based on DWT and FCT. (2021). Iraqi Journal of Science, 58(4B), 2200-2210. https://doi.org/10.24996/ijs.2017.58.4B.23