Abstract: A digital image processing method for locating faces in a digital color image includes the steps of: generating a mean grid pattern element (MGPe) image from a plurality of sample face images; generating an integral image from the digital color image; and locating faces in the color digital image by using the integral image to perform a correlation between the mean grid pattern element (MGPe) image and the digital color image at a plurality of effective resolutions by reducing the digital color image to grid pattern element images (GPes) at different effective resolutions and correlating the MGPe with the GPes.

Abstract: A digital image processing method for locating eyes and mouth in a digital face image. The method includes the steps of detecting iris colored pixels in the digital face image; grouping the iris colored pixels into clusters; detecting eye positions using the iris colored pixels; identifying salient pixels relating to a facial feature in the digital face image; generating a signature curve using the salient pixels; and using the signature curve and the eye positions to locate a mouth position. In a preferred embodiment, a summation of squared difference method is used to detect the eye positions. In another preferred embodiment, the eyes and mouth positions are validated using statistics.

Abstract: A method for reconstructing computerized tomographic (CT) images of an object, including: scanning the object with a CT imaging system to acquire views that include measured projections of the object. Additionally, the method applies an iterative algorithm to minimize errors between the measured projections and reprojections of a reconstructed CT image, wherein at each iteration, projection errors become smaller causing the reconstructed CT image to become further refined.

Abstract: A method for securely transacting a transaction based on a transaction document having an image contained within the document, the method includes the steps of compressing an image on the document; scrambling the structure of the compressed image according to a permutation; obtaining the inverse permutation; applying the inverse permutation to the scrambled image for obtaining an unscrambled image; and decompressing the unscrambled image.

Abstract: A three-dimensional model of a scene is obtained from a plurality of three-dimensional panoramic images of a scene, wherein each three-dimensional panoramic image is derived from a plurality of range images captured from a distinct spatial position. Transformations are determined that align the plurality of three-dimensional panoramic images, and spatial information is integrated from the plurality of three-dimensional panoramic images to form a spatial three-dimensional model of the scene. Finally, intensity and texture information is integrated from the plurality of three-dimensional panoramic images onto the spatial three-dimensional model to form a three-dimensional model of the scene containing both spatial and intensity information.

Abstract: A method for determining the presence of a face from image data includes a face detection algorithm having two separate algorithmic steps: a first step of prescreening image data with a first component of the algorithm to find one or more face candidate regions of the image based on a comparison between facial shape models and facial probabilities assigned to image pixels within the region; and a second step of operating on the face candidate regions with a second component of the algorithm using a pattern matching technique to examine each face candidate region of the image and thereby confirm a facial presence in the region, whereby the combination of these components provides higher performance in terms of detection levels than either component individually.

Abstract: A method for generating a stabilized three-dimensional image from a scannerless range imaging system comprises the steps of acquiring a bundle of three or more phase offset images corresponding to modulated illumination reflected from a scene, whereby one or more of the phase offset images includes image motion relative to another phase offset image; searching for a stable chain of phase offset images in the image bundle, wherein a stable chain is a collection of images that is obtained by testing the phase offset images against a confidence measure that separates less severe correctable image motion from more severe image motion and then populating the stable chain only with those phase offset images that meet the confidence measure for correctable image motion; correcting for the image motion in the stable chain of images if a stable chain of at least three phase offset images is found to exist; and computing a stabilized three-dimensional image using the phase offset images from the stable chain of phase o

Abstract: A digital image processing method is taught for detecting human irises in a digital image. The method comprises the steps measuring the red intensity of the pixels in the image, determining the probability that each pixel is an iris based upon the red intensity of the pixel, determining the probability that each pixel is not an iris based upon the red intensity of the pixel; and determining whether the pixel is an iris by analyzing the relationship between the probability that the pixel is an iris and the probability that the pixel is not an iris. In one embodiment of the present invention, the determination as to whether a pixel is an iris pixel is then made based upon the application of a Bayes model to the probability that the pixel is not an iris, the probability of the occurrence of an iris in the identified region and probability of the occurrence of a non-iris pixel in the identified region.

Abstract: A method for generating a range image sequence from a scannerless range imaging system of the type comprising an illuminator for illuminating a scene with modulated illumination; an image modulating component for receiving and modulating the modulated illumination reflected from the scene; an image capture element for capturing images output by the image modulating component, including an image bundle of at least three phase offset images each incorporating a phase delay corresponding to the distance of objects in the scene from the illuminator, wherein each phase offset image of an image bundle also incorporates a phase offset distinct for each image. According to the method, a sequence of three or more phase offset images are acquired that correspond to the modulated illumination reflected from the scene, whereby the sequence contains overlapping subsequences of successive phase offset images, each subsequence forming an image bundle.

Abstract: A color scannerless range imaging system comprises four component systems, including an illumination system, an image capture device, an optical assembly and a controller for interconnecting and controlling the component systems. The illumination system separately illuminates a scene with modulated and unmodulated illumination, while the image capture device is positioned in an optical path of the reflected illumination from the scene for capturing a plurality of images thereof, including (a) at least one image of the reflected modulated illumination, whereby the modulation of the reflected modulated illumination incorporates a phase delay corresponding to the distance of objects in the scene from the range imaging system, and (b) at least one color image of the reflected unmodulated illumination.

Abstract: A scannerless range imaging system employs a technique for embedding digital data into its image output in a manner that allows exact recovery of its associated images. The range imaging system captures (a) a plurality of phase images of reflected modulated illumination, wherein each image incorporates a phase delay term corresponding to the distance of objects in the scene from the range imaging system, together with a phase offset term unique for each image, and (b) at least one intensity image of reflected unmodulated illumination, and then generates an image bundle of associated images including the plurality of phase images and the intensity image.

Abstract: A method of embedding information in an image or video, comprising associating information with a affine transformation, inducing the effect of the affine transformation on an array of steganographically encoded signals, to form a transformed steganographic signal and combining the transformed steganographic signal with an image or video. Furthermore, a method of extracting information from a transformed steganographic signal embedded in an image or video, comprising autocorrelating the embedded image or video to determine an induced affine transformation and using the determined affine transformation as an index into a database containing information.

Abstract: Intermediate panoramic images are each generated from two original panoramic images, where each panoramic image provides a 360 degree field of view of a scene from different nodal points. First, pairs of planar images are derived, where each pair corresponds to original planar views derived from respective portions of the original panoramic images, where a similar area of the scene is visible from each pair of planar views. Then, an intermediate planar image is generated from each pair of planar images, and the resulting series of intermediate planar images are cylindrically concatenated to form the intermediate panoramic image.

Abstract: The present invention comprises a digital image processing method for detecting human eyes in a digital image. This method comprises the steps of: detecting iris pixels in the image; clustering the iris pixels, and selecting at least one of the following methods to identify eye positions: applying geometric reasoning to detect eye positions using the iris pixel clusters; applying a summation of squared difference method using the iris pixel clusters to detect eye positions; and applying a summation of squared difference method to detect eye positions from the pixels in the image. The method applied is selected on the basis of the number of iris pixel clusters. In another embodiment, the present invention also comprises a computer program product.

Abstract: A method for generating a range image sequence from a scannerless range imaging system of the type comprising an illuminator for illuminating a scene with modulated illumination; an image modulating component for receiving and modulating the modulated illumination reflected from the scene; an image capture element for capturing images output by the image modulating component, including an image bundle of at least three phase offset images each incorporating a phase delay corresponding to the distance of objects in the scene from the illuminator, wherein each phase offset image of an image bundle also incorporates a phase offset distinct for each image.

Abstract: A digital image processing method for determining an orientation of a face in a digital color image generates a mean grid pattern element image from a plurality of sample face images and an integral image from the digital color image. A face is located in the color digital image by using the integral image to perform a correlation test between the mean grid pattern element image and the digital color image at a plurality of effective resolutions by reducing the digital color image to a plurality of grid pattern element images at different effective resolutions and correlating the mean grid pattern element image with the plurality of grid pattern element images, whereby either the mean grid pattern element image or the grid pattern element images are provided at a plurality of different orientations. Accordingly, an orientation of the face in the color digital image is determined by using the images with different orientations in the correlation test.

Abstract: In a method of obtaining an extended dynamic range panorama of a scene from a plurality of limited dynamic range images captured by an image sensor in a digital camera, a plurality of digital images comprising image pixels of the scene are captured from a plurality of positions by exposing the image sensor to light transmitted from the scene, wherein light transmittance upon the image sensor is adjustable. Each image is evaluated after it is captured for an illumination level exceeding the limited dynamic range of the image for at least some of the image pixels. Based on the evaluation of each image exceeding the limited dynamic range, the light transmittance upon the image sensor is adjusted in order to obtain a subsequent digital image having a different scene brightness range.

Abstract: A computer vision/image processing method of removing blond hair color pixels in digital image skin detection for a variety of imaging related applications, such as redeye defects detection, employs a combination of skin detectors operating in a generalized RGB space in combination with a hue space derived from the original image space to detect skin pixels and blond hair pixels within the skin pixels.

Abstract: A scannerless range imaging system includes an illumination system for illuminating a scene with modulated illumination of a predetermined modulation frequency, and an image intensifier receiving reflected modulated illumination and including a modulating stage for modulating the reflected modulated illumination from the scene with the predetermined modulation frequency. An image responsive element includes an array of individual pixels for capturing images output by the image intensifier, whereby the modulation of the reflected modulated illumination incorporates a phase delay corresponding to the distance of objects in the scene from the range imaging system. A transmittance filter, including a plurality of filter elements having a spatially varying pattern of transmittance, are arranged in a one-to-one mapping with respect to the pixels forming the image responsive element.

Abstract: A method for detecting skin color in a digital image having pixels in an RGB color space generally includes the steps of performing statistical analysis of the digital color image to determine the mean RGB color values; then, if the mean value of any one of the colors is below a predetermined threshold, applying a transformation to the digital image to move skin colors in the image toward a predetermined region of the color space; and employing the transformed space to locate the skin color pixels in the digital color image. More specifically, if the mean value of any one of the colors is below a predetermined threshold, a non-linear transformation is applied to the digital image to move skin colors in the image toward a predetermined region of the color space.