1. A method for classifying a candidate red-eye object in a digital image, the method comprising the acts of: i) selecting a candidate red-eye object in a digital image; ii) determining the number of subwindows of the selected candidate red-eye object passed through an AdaBoost classifier for a certain classification stage; iii) calculating a ratio between either: iii.a) the number of subwindows passed through a current stage and the number of subwindows passed through a previous stage; or iii.b) the number of subwindows passed through the current stage and the difference between the total number of subwindows to be tested by the AdaBoost classifier and the number of subwindows passed through the previous stage; iv) determining that the ratio is greater than or equal to a stage threshold; and v) transforming the candidate red-eye object into a true red-eye object.