Abstract: In an exemplary embodiment of the present invention, an image processor is provided. According to a feature of the present invention, the image processor comprises a CPU arranged and configured to receive an image input, the image input depicting a scene, the CPU being further arranged and configured to execute a routine to receive the image input and perform preselected spatio-spectral analysis of the image to create a version of the image input optimized for analysis of the scene.

Abstract: In a first exemplary embodiment of the present invention, an automated, computerized method is provided for processing an image. According to a feature of the present invention, the method comprises the steps of generating a gradient representation of the image, and normalizing the gradient representation to generate an illumination-invariant gradient representation of the image.

Abstract: In a first exemplary embodiment of the present invention, an automated, computerized method is provided for determining an illumination flux condition in a scene. The method comprises the steps of generating and storing a sequence of images of the scene, each one of the sequence of images comprising an array of pixels and corresponding to the scene photographed in a preselected polarization direction, different from the polarization direction of other ones of the sequence of images, determining a polarization sequence vector for at least one pixel in the array, as a function of color information for the pixel in the array, among the sequence of images; and utilizing the polarization sequence vector to determine one of a shadowed and lit illumination condition for the at least one pixel.

Abstract: In a first exemplary embodiment of the present invention, a camera is provided. The camera comprises a lens and a sensor to record an image focused by the lens in N color bands, wherein N equals a number of color bands, with the number and respective locations and widths of the N color bands being selected to optimize the image for processing.

Abstract: In a first exemplary embodiment of the present invention, an automated, computerized method for learning object recognition in an image is provided. According to a feature of the present invention, the method comprises the steps of providing a training set of standard images, calculating intrinsic images corresponding to the standard images and building a classifier as a function of the intrinsic images.

Abstract: In a first exemplary embodiment of the present invention, an automated, computerized method is provided for determining illumination information in an image. According to a feature of the present invention, the method comprises the steps of identifying depth information in the image, identifying spatio-spectral information for the image, as a function of the depth information and utilizing the spatio-spectral information to identify illumination flux in the image.

Abstract: In a first exemplary embodiment of the present invention, an automated, computerized method is provided for determining illumination flux in an image. According to a feature of the present invention, the method comprises the steps of performing a computer learning technique to determine spatio-spectral information for the images, and utilizing the spatio-spectral information to identify illumination flux.

Abstract: In an exemplary embodiment of the present invention, an automated, computerized method is provided for classifying pixel values in a motion sequence of images. According to a feature of the present invention, the method comprises the steps of determining spectral information relevant to the sequence of images, and utilizing the spectral information to classify a pixel as one of background, shadow and object.