Translating contemporary Turkish to Ottoman Turkish by using artificial neural network based optical character recognition

In this study, translation of current Turkish characteristics into Ottoman Turkish is performed by using artificial neural Optical Character Recognition. This study consists of two phases. The first phase is after recognized any character on the image which will be known and will be separated. Another step is separated characters will be converted to ottoman language. In that first step were used neural artificial networks that belongs to OCR system, artificial intelligence illiterately; the theory and development of computer systems able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages. Subset of the artificial intelligence which is some of them is a neural artificial networks were gotten as idea of the human brain system, it include kind of microprocessor technology. In this technology were preferred expansionary networks as web structure and inside this technology there are some different technics effects perfectly such as image process techniques. In this study neural artificial networks were tested perfectly and applied on the study also all characters were separated intensively. Trained network recognizes the separated characters respectively. Dedicated words is translated by structure of the ottoman language grammar. Such as for sound of a "ا" (elif), for sound of e "ه" (he) for sounds of o,ö,ü,u "و " (vav) for sound of ı, i "ی" (ye) and another mentioned words is translated Arabic and Persian grammar structures.