HANDWRITTEN CHARACTER RECOGNITION

Abstract

Handwritten characters are seen everywhere in our day-to-day life. Almost all the things we do involve letters, from writing cheques to writing notes manually. Handwritten character recognition is considered as a core to a diversity of emerging application by using the concepts of machine learning. It is used widely for performing practical applications such as reading computerized bank cheques. However, executing a computerized system to carry out certain types of duties is not easy and it is a challenging matter. There is huge variability and ambiguity of strokes from person to person. Handwriting style of an individual person also varies from time to time and is inconsistent. There are many challenges which we have to deal with while understanding handwritten text. Poor quality of the source document/image due to degradation over time can affect the way of understanding the characters. However, we can find a solution for this using machine learning. This paper illustrates a model which interprets handwritten character accurately with the help of data set which we used to train the data model. The main objective of this paper is to ensure effective and reliable approaches for recognition of handwritten characters.