Abstract: A method for normalizing the lighting changes in an input image made up of an X and Y array of pixels having various illuminating intensities, wherein the lighting changes having an additive effect and a multiplicative effect on the input image. The method comprises the steps of estimating the additive effect from the input image to provide a background estimate; estimating the multiplicative effect from the input image to provide a gain estimate; subtracting the background estimate from the image; and normalizing the image with respect to the gain estimate. Also described is an apparatus for automatically determining the identity of an image. The apparatus comprises video camera for acquiring the image to be recognized and a light normalizer coupled to the video camera for normalizing lighting changes in the image and producing a normalized image which can be more accurately recognized.

Abstract: A detection system identifies a person by rapidly analyzing an image frame from a video camera for the presence of a face by reducing the image in resolution and normalizing the image to compensate for lighting changes and compares the normalized image with a background image to produce a binary interest mask. The most likely position of a face is then determined by identifying a top, bottom and sides of a possible head region to define a bounding box, normalizing the pixel data within the bounding box to further compensate for lighting variations, and resizing the box to match identification templates stored in memory. The best match from the identification templates is provided with a score indicative of the degree of the match. If the score does not exceed a first score threshold, then no face is assumed present. If the score exceeds a first and second score threshold, then a face is assumed present.