Affiliation:
1. MIT Arts, Design and Technology University, Pune, India
Abstract
Handwritten text detection refers to the capacity of a computer system to interpret and understand handwritten input from various sources such as paper documents, touch displays, and photographs. Within the realm of pattern recognition, one specific area is handwritten text recognition, which involves categorizing and interpreting handwritten text. In this study, we propose a novel approach to offline handwritten text recognition utilizing deep neural networks. The availability of vast amounts of data and continuous algorithmic enhancements have made training neural networks more accessible than ever before. This handwritten character recognition system relies on image segmentation to accurately identify and interpret handwritten characters. Through this approach, we aim to improve the accuracy and efficiency of recognizing handwritten text across various applications and contexts.