Online Kannada Handwritten Characters and Numerical Recognition using CNN Classifier
M H Gandhana, L. Ananth Naik · Zenodo (CERN European Organization for Nuclear Research) · 2021
The objective of this paper is to recognize Kannada handwritten characters and numerals in a real-time application using CNN classifier. The data acquisition technique entails the capturing of data using a Graphics tablet that has 5080LPI resolution and an XP stylus pen. The sensor take-up the pointing and pen-up, pen-down and bobbing movement of the pen. Kannada manuscript includes 52 syllabary characters, these divided into 14 Vowels, 36 Consonants, 2 Special characters also 10 Kannada numerals 3100(62x50) dataset are used. Convolutional Neural Network(CNN) classifier used for character recognition purpose, training and testing of dataset carried out by CNN model. This proposed model provides 97.09% of testing accuracy and 0.212% as less testing error.