Indian Journal of Science and Technology

Abstract

Objectives: A framework for character recognition is essential used to convert a digital image of character into machine coded format character. This fundamental trademark can be used to determine numerous real life applications. Methods/ Statistical Analysis: To classify hand-written documents, either offline or online, the recognition of character is tremendously influenced by variety of styles of same writer on various circumstances and even different writers. Distortion and noise included during digitization is additionally a noteworthy issue in recognition of character that influences the recognition/classification accuracy adversely. Findings: It has been get to know that recognition of hand-written Gurmukhi characters is an exceptionally troublesome task. There are enormous difficulties in handwritten character recognition because of various writing style of scholars. This paper presents various techniques presented by different researchers for Punjabi character recognition work. It has been also noticed that recognition accuracy depends upon volume of training dataset and testing dataset and may be improved by using various optimized feature selection techniques. Application/ Improvements: A lot of research papers have been surveyed and it is seen that work on different strategies have been attempted.

Keywords: Classification, Document Analysis and Recognition, Feature Extraction, Optical Character Recognition