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Image classification is an ongoing research challenge. Most of the availableresearch focuses on image classification for the English language, howeverthere is very little research on image classification for the Arabic language.Expanding image classification to Arabic has several applications. The presentstudy investigated a method for generating Arabic labels for images of objects.The method used in this study involved a direct English to Arabic translationof the labels that are currently available on ImageNet, a database commonlyused in image classification research. The purpose of this study was to testthe accuracy of this method. In this study, 2,887 labeled images were randomlyselected from ImageNet. All of the labels were translated from English toArabic using Google Translate. The accuracy of the translations was evaluated.Results indicated that that 65.6% of the Arabic labels were accurate. Thisstudy makes three important contributions to the image classificationliterature: (1) it determined the baseline level of accuracy for algorithmsthat provide Arabic labels for images, (2) it provided 1,895 images that aretagged with accurate Arabic labels, and (3) provided the accuracy oftranslations of image labels from English to Arabic.

Image Classification for Arabic: Assessing the Accuracy of Direct English to Arabic Translations