This paper proposes a deep learning approach to recognize Tamil Letter from images which contains text. This is recognition process, the text in the images are divided to letter or characters. Each recognized letters are sending to recognition system and filter the text using deep learning algorithms. Our proposed algorithm is used to separate letter from the text using convolution neural network approach. The filtering system is used for identifying font based on that letters are found. The Tamil letters are test data and loaded in recognition systems. The trained data are input which contains filtered letter from image. For example, Tamil letters such as are available in test dataset. The trained data are applied into deep convolution neural network process. The two dataset are created which contains test data with Tamil letter and second one for recognized input data or trained data. 15 thousands of letters are taken and 512 X 512 X 3 size deep convolution network is created with font and letters. As the result, 85% Tamil letters are recognized and 82% are tested using font. TensorFlow is used for testing the accuracy and success rate.

Sridharan, M., Rani Arulanandam, D. C., Chinnasamy, R. K., Thimmanna, S., & Dhandapani, S. (2021). Recognition of font and tamil letter in images using deep learning. Applied Computer Science, 17(2), 90-99. https://doi.org/10.23743/acs-2021-15

Sridharan, Manikandan, Delphin Carolina Rani Arulanandam, Rajeswari K Chinnasamy, Suma Thimmanna, and Sivabalaselvamani Dhandapani. "Recognition of Font and Tamil Letter in Images Using Deep Learning." Applied Computer Science 17, no. 2 (2021): 90-99.

M. Sridharan, D. C. Rani Arulanandam, R. K. Chinnasamy, S. Thimmanna, and S. Dhandapani, "Recognition of font and tamil letter in images using deep learning," Applied Computer Science, vol. 17, no. 2, pp. 90-99, 2021, doi: 10.23743/acs-2021-15.

Sridharan M, Rani Arulanandam DC, Chinnasamy RK, Thimmanna S, Dhandapani S. Recognition of font and tamil letter in images using deep learning. Applied Computer Science. 2021;17(2):90-99.