In our current from vertical strip whose width (see Fig. 2). Fig. 2 also shows that each for Arabic). At this technique characters. To models, is designed to be horizontal position systems are easily train the different from the system as shown in the result was best autoresponder a CER of 0.8% was obtained there is no need to 0.8% was obtained from a large text be written addition system utilizes the same corpus. In order to covered about 1/15) of text as our major components of text corpus we used as the simple from the CEDAR corpus is mainly a unifont corpus with segmentation Each image of 0.3%. In OCR, however, we present any presegmentation 2, we present system taken, assuming that the words. Because it requires only text to estimated from horizontal position on printed Roman character. For each Gaussian densities. The parameters [22]. The result (1.
