This paper presents a very fast multi-stage algorithm for the recognition of non-Latin script. Although the examples use Arabic script, the system could be adapted in minutes to deal with any character set, in particular non-Latin characters where no commercial OCR systems are available. The approach used normalises isolated characters for size and extracts an image signature based on the number of black pixels in the rows and columns of the character and compares these values to a set of signatures for typical characters of the set. This technique identifies not only the closet match but gives the closeness of match to all other characters in the set, which is expressed in a triangular Confusion Matrix.