Character Recognition System for Devanagari Script Using Machine Learning Approach
Shilpa Mangesh Pande, Bineet Kumar Jha · 2021
It is a very difficult task to manually process the handwritten documents due to varieties of handwritten scripts and lack of associated language dictionary to interpret documents. Most of the large companies as well as small-scale industries want to automate the process of script recognition. The big challenge is to make machines recognize the hand-printed scripts. Humans can recognize handwritten or hand-printed words after gaining knowledge of a specific language. In the same way, machines should be trained to recognize the handwritten scripts. This process of transferring human knowledge to computers should be automated. The proposed research work attempts to automate the character recognition system for Devanagari script using various machine learning classifiers like Decision Tree classifier, Nearest Centroid classifier, K Nearest Neighbors classifier, Extra Trees classifiers and Random Forest classifier. The performance of all the classifiers is evaluated using accuracy parameter as success criteria. The Extra Trees classifiers and Random Forest classifier is proved to better than other classifiers with 78% and 77% of accuracy respectively. The robustness to picture quality, writing style, font size is the novelty of the OCR system which makes it ideal to use.