A View-Based Toeplitz-Matrix-Supported System for Word Recognition without Segmentation

In this paper, new modifications and experiments for word recognition and classification are presented. The algorithm is based on recognizing the whole words without separating them into letters. The whole word is treated and analyzed as an image. The method is based on the modification of a novel view-based word recognition algorithm - an approach that was successfully used by the authors' in previous works. This method shows how to recognize words without segmentation. The top and bottom views of the word are analyzed in order to create the feature vector. Then the feature vector is processed by the aid of Toeplitz matrices. The obtained series of Toeplitz matrix minimal eigenvalues are used for classification. The results are promising