An Efficient Method for Bangla Handwritten Digit Recognition Using Convolutional Neural Network
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Abstract
Handwritten digit recognition is a fundamental problem in the field of computer vision and pattern recognition. This paper presents a Convolutional Neural Network (CNN) approach for recognizing handwritten Bangla digits. The proposed method utilizes a dataset of handwritten Bangla digit images and trains a CNN model to classify these digits accurately. The dataset is preprocessed to enhance the quality of the images and make them suitable for training the CNN model. The trained model is then tested on a separate test dataset to evaluate its performance in terms of accuracy. With the Ekush: Bangla Handwritten Data - Numerals dataset, we tested our CNN implementation to determine the precision of handwritten characters. According to the test results, 25% of the images using a training set of more than 150,000 images from Ekush dataset had an accuracy of 98.3%.
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References
Khandokar, I., Hasan, M., Md, Ernawan, F., Islam, S., Md, & Kabir, M. N. (2021). Handwritten character recognition using convolutional neural network. In Journal of Physics: Conference Series (Vol. 1918, Issue 4, p. 042152). IOP Publishing. https://doi.org/10.1088/1742-6596/1918/4/042152.
Gu, J., Wang, Z., Kuen, J., Ma, L., Shahroudy, A., Shuai, B., Liu, T., Wang, X., Wang, L., Wang, G., Cai, J., & Chen, T. (2015). Recent Advances in Convolutional Neural Networks (Version 6). arXiv. https://doi.org/10.48550/ARXIV.1512.07108.
Ptucha, R., Petroski Such, F., Pillai, S., Brockler, F., Singh, V., & Hutkowski, P. (2019). Intelligent character recognition using fully convolutional neural networks. In Pattern Recognition (Vol. 88, pp. 604–613). Elsevier BV. https://doi.org/10.1016/j.patcog.2018.12.017.
Farabet, C., Couprie, C., Najman, L., & LeCun, Y. (2013). Learning hierarchical features for scene labeling. IEEE transactions on pattern analysis and machine intelligence, 35(8), 1915-1929.
Rashid, M. M., Rokon, I., Ahmed, T., & Islam, M. R. (2020). Performance Evaluation of Various Feature Extraction Techniques for Handwritten Bangla Digit Recognition. In 2020 12th International Conference on Software, Knowledge, Information Management and Applications (SKIMA) (pp. 1-6). IEEE.
Md Zahangir Alom, Paheding Sidike, Mahmudul Hasan, Tarek M. Taha, Vijayan K. Asari, "Handwritten Bangla Character Recognition Using the State-of-the-Art Deep Convolutional Neural Networks", Computational Intelligence and Neuroscience, vol. 2018, Article ID 6747098, 13 pages, 2018. https://doi.org/10.1155/2018/6747098.
M. Al Rabbani Alif, S. Ahmed and M. A. Hasan, "Isolated Bangla handwritten character recognition with convolutional neural network," 2017 20th International Conference of Computer and Information Technology (ICCIT), 2017, pp. 1-6, doi: 10.1109/ICCITECHN.2017.8281823..
R. R. Chowdhury, M . S. Hossain, R. ul Islam, K. Andersson and S. Hossain, "Bangla Handwritten Character Recognition using Convolutional Neural Network with Data Augmentation," 2019 Joint 8th International Conference on Informatics, Electronics & Vision (ICIEV) and 2019 3rd International Conference on Imaging, Vision & Pattern Recognition (icIVPR), 2019, pp. 318-323, doi: 10.1109/ICIEV.2019.8858545.
Mohammad Meraj Khan, Mohammad Shorif Uddin, Mohammad Zavid Parvez, Lutfur Nahar, A squeeze and excitation ResNeXt-based deep learning model for Bangla handwritten compound character recognition, Journal of King Saud University Computer and Information Sciences, 2021, ISSN 1319 -1578, https://doi.org/10.1016/j.jksuci.2021.01.021.
Hazra, A., Choudhary, P., Inunganbi, S. et al. Bangla-Meitei Mayek scripts handwritten character recognition using Convolutional Neural Network. Appl Intell 51, 2291–2311 (2021). https://doi.org/10.1007/s10489-020-01901-2.
C. Saha, R. H. Faisal and M. M. Rahman, "Bangla Handwritten Basic Character Recognition Using Deep Convolutional Neural Network," 2019 Joint 8th International Conference on Informatics, Electronics & Vision (ICIEV) and 2019 3rd International Conference on Imaging, Vision & Pattern Recognition (icIVPR), 2019, pp. 190-195, doi: 10.1109/ICIEV.2019.8858575.
S. Alam, T. Reasat, R.M. Doha, and A.I Humayun, “NumbtaDB Assembled Bengali Handwritten Digits”, arXiv:1806.02452[cs.CV], 6 June, 2018.
C. Saha, R. H. Faisal and M. Mostafijur Rahman, "Bangla Handwritten Character Recognition Using Local Binary Pattern and Its Variants," 2018 International Conference on Innovations in Science, Engineering and Technology (ICISET), 2018, pp. 236-241, doi: 10.1109/ICISET.2018.8745645.
R. Noor, K. Mejbaul Islam and M. J. Rahimi, "Handwritten Bangla Numeral Recognition Using Ensembling of Convolutional Neural Network," 2018 21st International Conference of Computer and Information Technology (ICCIT), 2018, pp. 1 -6, doi: 10.1109/ICCITECHN.2018.8631944.
M. Shopon, N. Mohammed and M. A. Abedin, "Bangla handwritten digit recognition using autoencoder and deep convolutional neural network," 2016 International Workshop on Computational Intelligence (IWCI), 2016, pp. 64-68, doi: 10.1109/IWCI.2016.7860340.
T. Hassan and H. A. Khan, "Handwritten Bangla numeral recognition using Local Binary Pattern," 2015 International Conference on Electrical Engineering and Information Communication Technology (ICEEICT), 2015, pp. 1-4, doi: 10.1109/ICEEICT.2015.7307371.
Rabby, A. S. A., Haque, S., Islam, Md. S., Abujar, S., & Hossain, S. A. (2019). Ekush: A Multipurpose and Multitype Comprehensive Database for Online Off-Line Bangla Handwritten Characters. In Communications in Computer and Information Science (pp. 149–158). Springer Singapore. https://doi.org/10.1007/978-981-13-9187-3_14.
Huda, Hasibul & Fahad, Md & Islam, Moonmoon & Das, Amit. (2022). Bangla Handwritten Character and Digit Recognition Using Deep Convolutional Neural Network on Augmented Dataset and Its Applications. 1-7. 10.1109/IMCOM53663.2022.9721634.
R. A. Tuhin, B. K. Paul, F. Nawrine, M. Akter and A. K. Das, "An Automated System of Sentiment Analysis from Bangla Text using Supervised Learning Techniques," 2019 IEEE 4th International Conference on Computer and Communication Systems (ICCCS), Singapore, 2019, pp. 360-364.