Classification and interpretation of characters in multi-application OCR system

A great deal of computer vision research and study is dedicated to the systems designed to detect and analyze computer printed documents and human written text. Optical Character Recognition (OCR) refers to the process of converting images of hand-written, typewritten, or printed text into a format understood by machines for the purpose of editing, indexing/searching, and a reduction in storage size. In this paper we have combined the functionality of Optical Character Recognition and have focused on its applications like Image Sudoku Solver, Car License Plate Detection and Recognition, Handwritten and Computer Printed Documents Recognition. This paper develops a user friendly application for performing image to text conversion. The developed system is organized as a set of modules, each dedicated to a specific application. Car License Plate Detection and Recognition system extracts out the License plate accurately and produce an effective recognition of the characters in the License Plate. With the proposed methodology, we have been able to achieve results with 96% accuracy for the tested images. Image Sudoku Solver is intended to work with Sudoku Puzzle images by extracting out the numbers, boundaries from them and then solving the puzzle. In this we are able to extract, recognize and solve around 98% of Sudoku Puzzles being tested for the purpose. Online Handwriting Recognition accomplishes the real time recognition of user´s Handwriting from a Mouse or a Laptop Touchpad.