Naila Habib Khan1,*, Awais Adnan1, Abdul Waheed2,3, Mahdi Zareei4, Abdallah Aldosary5, Ehab Mahmoud Mohamed6,7
CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1347-1367, 2021, DOI:10.32604/cmc.2020.013715
Abstract Cursive text recognition of Arabic script-based languages like Urdu is extremely complicated due to its diverse and complex characteristics. Evolutionary approaches like genetic algorithms have been used in the past for various optimization as well as pattern recognition tasks, reporting exceptional results. The proposed Urdu ligature recognition system uses a genetic algorithm for optimization and recognition. Overall the proposed recognition system observes the processes of pre-processing, segmentation, feature extraction, hierarchical clustering, classification rules and genetic algorithm optimization and recognition. The pre-processing stage removes noise from the sentence images, whereas, in segmentation, the sentences are segmented into ligature components. Fifteen features… More >
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