A Review on Online and Offline Handwritten Gurmukhi Character Recognition
Tajinder Pal Singh, Sheifali Gupta, Meenu Garg · 2022 10th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO) · 2022
Various deep learning and machine learning algorithms are working to address existing problems in applications of pattern recognition and natural language processing. Handwritten text recognition is one of those applications which have major concerns. In handwritten text recognition, a large body of research work has already been reported for non-Indian scripts, but it's not so for Indian scripts. The same is applicable to Gurmukhi. Gurmukhi is a northern Indian language and it is the fourteenth most spoken language in the world. Due to excessive cursiveness and structural similarity among the characters in Gurmukhi handwriting, text recognition is a complex research problem. Sometimes the quality recognizers don't give satisfactory results on it. In the present article, a review of online and offline handwritten character recognition techniques and their performance comparison is given in Gurmukhi script. Researchers working in the field of optical character recognition will find the in-depth analysis presented in this article useful in understanding when to employ which classifier for the best outcomes. A survey on the number of research publications in a particular time span (2008 to 2019) in Gurmukhi handwritten character recognition is also presented here.