Spectral features for Arabic word recognition

Authors:
M. S. Khorsheed;W. F. Clocksin
Affiliations:
Comput. Lab., Cambridge Univ., UK;-
Venue:
ICASSP '00 Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 06
Year:
2000

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Abstract

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.