||The use of automatic number plate recognition (ANPR) is crucial in many traffic surveillance applications. One step in an ANPR application is the optical character recognition (OCR) where a computer interprets images of characters as text. This master thesis presents an OCR method for an ANPR application on Swedish number plates. In this application the assumption is made that the position of the number plate in the image is known. Character recognition was achieved by applying template matching on the greylevel of the original image. The method was implemented and tested on 217 images from nine datasets with different characteristics. The percentage of correctly read number plates, assuming a standard number plate context, i.e., three letters and then three digits, was 48%. When not assuming a standard number plate context, i.e., including the letters Å, Ä and Ö and allowing 2 to 7 characters, the accuracy was 24%. Some characters were found to be difficult for the method to differentiate between when using a standard number plate context, e.g., “6'', “5'' and “8'', “D'' and “O'' and “F'' and “E''. When not assuming standard number plate context also the character sets “A'' and “Ä'' and, “D'', ”O'' and “0'' were hard for the method to separate.