Optical Script Identification for multi-lingual Indic-script

TL;DR

This paper surveys recent advancements in optical script identification and text recognition for multi-lingual Indic scripts, highlighting challenges and comparing algorithms to aid future research in complex script analysis.

Contribution

It provides a comprehensive comparison of current methods for Indic script identification and discusses advancements in preprocessing and recognition techniques.

Findings

Complex characteristics of Indic scripts pose recognition challenges.

Advanced preprocessing improves recognition accuracy.

Survey compares multiple algorithms for script identification.

Abstract

Script identification and text recognition are some of the major domains in the application of Artificial Intelligence. In this era of digitalization, the use of digital note-taking has become a common practice. Still, conventional methods of using pen and paper is a prominent way of writing. This leads to the classification of scripts based on the method they are obtained. A survey on the current methodologies and state-of-art methods used for processing and identification would prove beneficial for researchers. The aim of this article is to discuss the advancement in the techniques for script pre-processing and text recognition. In India there are twelve prominent Indic scripts, unlike the English language, these scripts have layers of characteristics. Complex characteristics such as similarity in text shape make them difficult to recognize and analyze, thus this requires advance preprocessing methods for their accurate recognition. A sincere attempt is made in this survey to provide a comparison between all algorithms. We hope that this survey would provide insight to a researcher working not only on Indic scripts but also other languages.