Rapid image binarization with morphological operators

In a grayscale image to be binarized, some pixels represent "foreground" text, to be converted to black-while others represent a shaded "background" region, to be converted to white. The difference between the two is largely one of scale. Morphological operators, the alternating sequential filter in particular, though an effective tool for extracting image background, are computationally expensive. We define reduced-complexity quick-open and quick-close morphological operators, which are employed to binarize grayscale images having complex backgrounds at modest computational cost.