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In this paper, we report on the use of characteristic loci features to cluster printed Farsi subwords, based on their holistic shapes. This yields a pictorial dictionary that can be used in a word recognition system to eliminate the search space. The feature vectors are compressed using PCA.The k-means algorithm is used to cluster 113,340 subwords of 4 fonts and 3 sizes to 300 clusters. The minimum...
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