In one aspect, the present invention is directed to a method for
object detection, the method comprising the steps of: dividing a
digital image into a plurality of sub-windows of substantially the same dimensions;
processing the image of each of the sub-windows by a
cascade of homogeneous classifiers (each of the homogenous classifiers produces a CRV, which is a value relative to the likelihood of a sub-window to comprise an image of the object of interest, and wherein each of the classifiers has an increasing accuracy in identifying features associated with the object of interest); and upon classifying by all of the classifiers of the
cascade a sub-window as comprising an image of the object of interest, applying a post-classifier on the
cascade CRVS, for evaluating the likelihood of the sub-window to comprise an image of the object of interest, wherein the post-classifier differs from the homogenous classifiers.