1. A method for automating an image rejection process, said method comprising: extracting features from at least one image among a batch of images utilizing an LBP (Local Binary Pattern) operator to train a classifier, said features comprising texture, spatial structure, and image quality characteristics, wherein said LBP operator extracts several different orientations and types of edge features in said at least one image, giving equal priority for all patterns found; calculating said features with respect to a test image for submission of said features to said classifier, given an operating point corresponding to a desired false positive rate; generating at least one output from said classifier as a confidence value corresponding to a likelihood of at least one of the following: a license plate being absent in said image, said license plate being unreadable, or said license plate being obstructed; and comparing said confidence value against a threshold to determine if said at least one image should be removed from a human review pipeline, thereby reducing images requiring human review.