1. A method for the detection and classification via an image processor of license plates displayed in images captured by an image-capturing unit, said method comprising: capturing an image of a vehicle utilizing an image-capturing unit that communicates with an image processor; locating a license plate region in said image of said vehicle after capturing said image with said image-capturing unit by extracting a set of candidate regions from said image utilizing a weak classifier of said image processor; ranking said set of candidate regions utilizing a secondary strong classifier of said image processor; and classifying said image according to a confidence driven classification based on classification criteria determined by said weak classifier and said secondary strong classifier, thereby automatically identifying and eliminating un-readable images from human review.
1. A method for the detection and classification via an image processor of license plates displayed in images captured by an image-capturing unit, said method comprising: capturing an image of a vehicle utilizing an image-capturing unit that communicates with an image processor; locating a license plate region in said image of said vehicle after capturing said image with said image-capturing unit by extracting a set of candidate regions from said image utilizing a weak classifier of said image processor; ranking said set of candidate regions utilizing a secondary strong classifier of said image processor; and classifying said image according to a confidence driven classification based on classification criteria determined by said weak classifier and said secondary strong classifier, thereby automatically identifying and eliminating un-readable images from human review. 4. The method of claim 1 wherein said secondary strong classifier comprises a neural network.