A Framework for Quick Rejection of Dissimilar Binary Images

Abstract

Given two binary images, how can we determine if the images are different? The most common technique used in the image processing arena is to calculate the correlation between the two images or simply subtract the two images. Both of these methods require some type of operation to be applied to the whole image. This implies that as the image size increases, more time will be required. In this paper, we show that -regardless of image size- only a limited number of points need to be checked to arrive at a required confidence level that the images are different. In fact, for completely different binary images only 8 points need to be checked to arrive at a 99% confidence level, 11 points need to be checked to arrive at a 99.9% confidence level and only 15 points need to be checked to arrive at a 99.99% confidence level. As a result, this method is magnitudes faster than traditional methods. Tests with real images are presented to show the validity of our technique. 