  Image classification is an ongoing research challenge. Most of the available
research focuses on image classification for the English language, however
there is very little research on image classification for the Arabic language.
Expanding image classification to Arabic has several applications. The present
study investigated a method for generating Arabic labels for images of objects.
The method used in this study involved a direct English to Arabic translation
of the labels that are currently available on ImageNet, a database commonly
used in image classification research. The purpose of this study was to test
the accuracy of this method. In this study, 2,887 labeled images were randomly
selected from ImageNet. All of the labels were translated from English to
Arabic using Google Translate. The accuracy of the translations was evaluated.
Results indicated that that 65.6% of the Arabic labels were accurate. This
study makes three important contributions to the image classification
literature: (1) it determined the baseline level of accuracy for algorithms
that provide Arabic labels for images, (2) it provided 1,895 images that are
tagged with accurate Arabic labels, and (3) provided the accuracy of
translations of image labels from English to Arabic.
