Fast real-time recognition and quality inspection of printed characters via point correlation

Some technical applications need a fast and reliable OCR for critical circumstances like low resolution and poor contrast. A concrete example is the real-time quality inspection system of Austrian banknotes. One requirement to the system is that it has to read two serial numbers on each banknote and to check if they are identical To solve the problem we have developed a novel method based an idea similar to pattern matching. However, instead of comparing entire images we use reduced sets of pixels, one for each different numeral. The detection is performed by matching these pixel sets with the corresponding pixels in the image being analyzed. We present an algorithm based on two cost functions that computes in a reasonable time the reduced pixel sets from a given set of image templates. The efficiency of our OCR has been increased considerably by introducing an appropriate set of image preprocessing operations. These are tailored especially to images with low resolution and poor contrast, bu they are simple enough to allow a fast real-time implementation. They can be seen as a normalization step that improves the image properties which are essential for pattern matching.