Bangla Character Recognitionusing Artificial Neural Network Step: FeatureSelection

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Show simple item record Debnath, Deepon Abdullah Al Mamun, Maj Md. Sarwar Hossain, Maj Md. 2015-06-28T06:17:45Z 2015-06-28T06:17:45Z 2013-12
dc.description We are thankful to Almighty Allah for his blessings for the successful completion of our thesis. Our heartiest gratitude, profound indebtedness and deep respect go to our supervisor Dr. Hasan Sarwar, Professor and Head of the Department, CSE, United International University, House: 80, Road: 8/A, Sat Masjid Road, Dhanmondi, Dhaka, Bangladesh, for his constant supervision, affectionate guidance and great encouragement and motivation. His keen interest on the topic and valuable advices throughout the study was of great help in completing thesis. We are especially grateful to the Department of Computer Science and Engineering (CSE) of Military Institute of Science and Technology (MIST) for providing their all out support during the thesis work. Finally, we would like to thank our families and our course mates for their appreciable assistance, patience and suggestions during the course of our thesis. en_US
dc.description.abstract Feature selection is an essential step of Optical Character Recognition. Accurate and distinguishable feature plays a significant role to leverage the performance of a classifier. The complexity level of feature identification algorithm differs for alphabet sets of different languages. Apart from generic algorithms to find features of different alphabet sets, these algorithmstakecareofindividualcharacteristiccommonforaparticularalphabetset. Dominant features of one alphabet set might completely differ from that of another set. Since there always remains the chance that inaccurate features may cause inefficient recognition, special attention should be given to identify the set of optimal features of a character set. Bengali characters also have some specific issues apart from the existing issues of other character sets. For example, there are about 300 basic, modified and compound character shapes in the script, the characters in a word are topologically connected, and Bengali is an inflectional language. Literature survey shows that several authors have used different features and classification algorithms. We have extensively reviewed all these feature sets. In order to identify an optimal feature set, variability analysis has been proposed here. We focused on the specific peculiarities of Bengali alphabet sets, its different usage as vowel and consonant signs, compound, complex and touching characters. We also took care to generate easily computable features that take less time for generation. en_US
dc.description.sponsorship Department of Computer Science and Engineering, Military Institute of Science and Technology en_US
dc.language.iso en en_US
dc.publisher Department of Computer Science and Engineering, Military Institute of Science and Technology en_US
dc.relation.ispartofseries B.Sc. in Computer Science and Engineering Thesis;
dc.subject Bangla,Character, Recognitionusing, Artificial, Neural, Network en_US
dc.title Bangla Character Recognitionusing Artificial Neural Network Step: FeatureSelection en_US
dc.type Thesis en_US

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