A Comparative study of Arabic handwritten characters invariant feature

TL;DR

This paper compares various feature extraction techniques for Arabic handwritten characters, highlighting their invariance properties to rotation and translation, with implications for improving recognition systems.

Contribution

It provides a comparative analysis of Hough, Fourier, Wavelet, and Gabor features regarding their invariance to rotation and translation in Arabic handwriting.

Findings

Hough Transform and Gabor filter are invariant to rotation and translation.

Fourier Transform is sensitive to rotation but invariant to translation.

Wavelet Transform is sensitive to both rotation and translation.

Abstract

This paper is practically interested in the unchangeable feature of Arabic handwritten character. It presents results of comparative study achieved on certain features extraction techniques of handwritten character, based on Hough transform, Fourier transform, Wavelet transform and Gabor Filter. Obtained results show that Hough Transform and Gabor filter are insensible to the rotation and translation, Fourier Transform is sensible to the rotation but insensible to the translation, in contrast to Hough Transform and Gabor filter, Wavelets Transform is sensitive to the rotation as well as to the translation.