In an earlier article about the methods of recognition of machine and hand-written cursive letters, we presented a model showing the possibility of processing, classifying, and hence recognizing such scripts as images. The practical results we obtained encouraged us to extend the theory to an algorithm for word recognition. In this article, we introduce our ideas, describe our achievements, and present our results of testing words for recognition without segmentation. This would lead to the possibility of applying the methods used in this work, together with other previously developed algorithms to process whole sentences and, hence, written and spoken texts with the goal of automatic recognition.