Spectral features for Arabic word recognition

We present a holistic technique for recognising words written in cursive Arabic script that does not rely on character segmentation. Each word is transformed into a normalised polar image, and a two dimensional Fourier transform is applied to the polar image. The resultant spectrum tolerates variations in size, rotation or displacement. Each word is represented by a single template, and the recognition is based on the Euclidean distance from those templates. Words are written in four different Arabic type-faces, where ligatures and overlaps pose challenges to segmentation-based methods