Feature extraction and classification techniques for handwritten Devanagari text recognition: a survey

The character recognition system is a vital area in the field of pattern recognition. One interesting, complex, and challenging task is handwritten character recognition because of various writing styles of individuals. The accuracy of such systems highly depends upon the extraction and selection of features. Many researchers proposed a variety of feature extraction and classification methods for various scripts including Devanagari. In view of that, this article presents a broad study of feature extraction and classification methods considered so far for online and offline Handwritten Character Recognition (HCR) for Devanagari script, which is essential in Optical Character Recognition (OCR) research. This article presents techniques used by authors, the dataset used, the accuracy achieved by the methods of the work already available for the OCR research. This article is depicting the latest studies, research gaps, challenges and future perspectives for the researchers working in the Devanagari text recognition domain. Moreover, methods developed for feature extraction and classification in the area of Devanagari character recognition are presented in a systematic way as an assistance for future researchers. It has been gathered that traditional feature extraction and classifications methods are being replaced with deep learning methods to achieve higher recognition accuracy in this area.