Degraded Character Image Restoration

The design and analysis of an algorithm for the restoration of degraded images of machine-printed characters is presented. The input is a set of degraded bilevel images of a single unknown character ; the output is an approximation to the charac-ter's ideal artwork. The algorithm seeks to minimize the discrepancy between the approximation and the ideal, measured as the worst-case Euclidean distance between their boundaries. We investigate a family of algorithms which superimpose the input images, add up the intensities at each point, and threshold the result. We show that, under degradations due to random spatial sampling error, signiicant asymp-totic improvements can be achieved by suitably pre-processing each input image and postprocessing the nal result. Experimental trials on special test shapes and Latin characters are discussed.