Hand Character Recognition Systems: A Review

Abstract

“Handwritten Char. Recognition”, is also known as “HCR”. It is a dynamic and developing area which has seen substantial improvements due to the use of in various areas. One of the exciting fields of machine learning and artificial intelligence is text detection. Numerous methods and techniques are used to classify characters. However, the techniques for translating textual content from a paper document into a machine-readable form were defined as preliminary studies and paperwork. The character recognition system may be a critical factor in establishing a paperless world by digitizing existing paper documents in the coming days. Numerous researches have been conducted in this field, but as handwriting styles differ from each human, it remained an active area of research. The biggest challenge is to obtain the highest possible character recognition accuracy rate, which will inevitably lead to a reduction in manual paperwork. The aim s to enhance handwriting text recognition s/w with a better accuracy, which makes it perfect, reducing the complexity of its space-time. Several papers have implemented a new diagonal-based feature extraction method, which generates a high precision rate than traditional feature extraction methods. This project aims at designing an expert system for HCR (English) using Neural Network. Using the Artificial Neural Network approach, this can effectively recognize a specific character of type format. This paper shows an overview of the field of recognition of Handwritten Text.