Farsi Machine-printed Subwords Recognition Using Contour-based Fourier Descriptors

Farsi Machine-printed Subwords Recognition Using Contour-based Fourier Descriptors

This paper presents a fast and simple method for Farsi/Arabic subwords recognition in a large lexicon. By omitting dots and complementary parts of machine-printed characters, a dataset including 9445 Farsi/Arabic subwords written by a single font and single size was obtained. This dataset not only reduces the number of subwords, but makes it suitable for both Farsi/Arabic languages. After normalizing boundary points of each subword, Fourier descriptor features are extracted. Experimental results on 30 plain text shows accuracy of 82.1% on subword level. Considering this large and comprehensive dataset, the obtained results are still promising which can be enhanced in the future by the use of Farsi/Arabic language grammar for connecting subwords.