HMM Based Approach for Online Arabic Script Based Languages Character Recognition
نویسنده
چکیده
-Arabic script based languages character recognition remains a challenging task due to its cursive nature. This task becomes more complex and demanding in case of handwritten Arabic script. We have used two layers HMM for recognition. We extracted directional and structural features for handwritten stroke and fused these feature to form more discriminant feature matrix. The fused feature matrix is used to find the critical point. The critical point is considered as a segmentation region. The segmented regions are then forward to HMM for character recognition. The second layer HMM is further used to recognize ligature. The two layers HMM provide 94.2% 98.8 % accuracy for character and ligature respectively.
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