Optical character recognition
This project enhances the character recognition system by using Linear Support Vector to enhance ease usability of programmed evaluation framework and improvise it with the help of SVM, Machine learning & Artificial intelligence.
Abstract
Handwriting Recognition has always played a prominant role in active and challenging area of research & development. Handwriting recognition system plays a significant part in today’s modern technological enhanced world. Handwriting recognition is very popular and has expensive computational executive work. In present time, it is very hard to find actual meaning of handwritten documents. There are plenty areas where it needs to recognise the correct words, alphabets and digits. Handwriting recognition has two basic type existing one is online and other is offline. In this project, by using Linear Support Vector we will present the handwriting recognition system in a very simple and feasible way. Different methods are studied and included it to enhance ease usability of programmed evaluation framework and improvise it with the help of SVM , Machine learning & Artificial intelligence & thus we enhance the character recognition system.