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All Journal IAES International Journal of Artificial Intelligence (IJ-AI)
Shah Tarik Nawaz
American International University-Bangladesh (AIUB)
Computer Science & IT Engineering

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A machine learning approach for Bengali handwritten vowel character recognition Shahrukh Ahsan; Shah Tarik Nawaz; Talha Bin Sarwar; M. Saef Ullah Miah; Abhijit Bhowmik
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 11, No 3: September 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v11.i3.pp1143-1152

Abstract

Recognition of handwritten characters is complex because of the different shapes and numbers of characters. Many handwritten character recognition strategies have been proposed for both English and other major dialects. Bengali is generally considered the fifth most spoken local language in the world. It is the official and most widely spoken language of Bangladesh and the second most widely spoken among the 22 posted dialects of India. To improve the recognition of handwritten Bengali characters, we developed a different approach in this study using face mapping. It is quite effective in distinguishing different characters. The real highlight is that the recognition results are more efficient than expected with a simple machine learning technique. The proposed method uses the Python library Scikit-Learn, including NumPy, Pandas, Matplotlib, and support vector machine (SVM) classifier. The proposed model uses a dataset derived from the BanglaLekha isolated dataset for the training and testing part. The new approach shows positive results and looks promising. It showed accuracy up to 94% for a particular character and 91% on average for all characters.
Co-Authors Abhijit Bhowmik M. Saef Ullah Miah Shahrukh Ahsan Talha Bin Sarwar