Handwritten Script and Word Recognition – A View-Based Approach

Abstract

This paper presents a hybrid system for character and word recognition. It is based on a modification to the view-based approach presented in authors’ previous works. The algorithm is appropriate for dealing with whole, unsegmented words or isolated characters. The characteristic vectors taken from views of the tested image are processed with the method of minimal eigenvalues of Toeplitz matrices. The obtained series of minimal eigenvalues are used for classification with Artificial Neural Networks. The results of the experiments on different sets of words and letters are presented.