• Chinmayee Bhat H

Handwriting character recognition (HCR) refers to a computer's ability to receive and interpret handwritten input. Handwritten Character Recognition is one of the most active and difficult research areas in Pattern Recognition. Pattern recognition is a process that utilises raw data to perform a task based on the category of the pattern. HCR is a well-known pattern recognition application. Due to a lack of research, handwriting recognition, particularly for Indian languages, is still in its infancy. The focus is to recognize the kannada handwritten character using machine learning algorithms such as KNN, SVM and deep learning algorithm(CNN). The data collection, data pre processing, feature extraction played a vital role in recognizing the character. KNN, SVM and CNN algorithm accuracy is obtained and compared. CNN gave the highest accuracy and it has been fed to GUI and thus character has been recognized.

Feature Extraction, Handwritten Character Recognition(HCR), KNN, SVM, CNN

"Kannada Hnadwritten Character Recognition Using KNN, SVM And CNN", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 8, page no.a454-a462, August-2022, Available :http://www.jetir.org/papers/JETIR2208060.pdf

"Kannada Hnadwritten Character Recognition Using KNN, SVM And CNN", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 8, page no. ppa454-a462, August-2022, Available at : http://www.jetir.org/papers/JETIR2208060.pdf