A Mutual Information Based Automatic Registration and Analysis Algorithm for Defect Identification in Printed Documents

In this paper, we propose a defect analysis system, which automatically aligns a digitized copy of a printed output to a reference electronic original and subsequently illustrates potential image quality artifacts. We focus on image defects or artifacts caused by shortfalls in mechanical or electrophotographic processes. In this method, log-polar transform and mutual information techniques are used for image registration. A confidence map is then calculated by comparing the contrast and entropy of the neighborhood for each pixel in both images. This confidence map results in a qualitative difference between printed documents and electronic originals. The algorithm was demonstrated successfully on a database of 94 images with 95.7% accuracy.