Abstract: A captured image is processed with one or more correction processes selected from a plurality of such processes, each associated with correction of a specific type of image defect, in order to improve the appearance of a viewed image generated from the captured image. Preliminary to the image processing, meta data related to image capture is obtained that is unique to each captured image, where the meta data is capable of indicating whether the specific types of image defects are likely to be present in the viewed image generated from the captured image.

Abstract: A method for processing a digital color image for display and transmission includes the steps of (a) resizing the image to a lower display resolution to produce a display-sized image, (b) quantizing the display-sized image to a display palette with an error diffusion process to produce an error diffused image, (c) losslessly compressing the error diffused image to produce a compressed image having a particular file size, (d) comparing the file size to a maximum file size and if less than the maximum file size, transmitting the digital image to the display; (e) if the file size is greater than the maximum file size but less than a another predetermined file size, reducing the error diffusion rate by a predetermined amount in order to reduce the file size; and (f) if the file size is greater than the maximum file size and the predetermined file size, simplifying the resized image by reducing image detail to produce a simplified image and repeating the preceding steps on the simplified 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: A method and apparatus for determining the best fit of a population mixture model to data. In the digital imaging area, the use of histogram data is employed. A plurality of sub-population functions are defined and then optimized to fit the data. An objective function is employed, which is based upon the parameters of the underlying functions. The number of underlying functions is added to the parameter mix, such that no a priori knowledge of the number of sub-populations is required. In an illustrative embodiment, a genetic algorithm is used to evolve the objective function to an optimal fit of the data. Once an optimal fit is found, through comparison with stopping criteria in a fitness function, the data is segmented according to threshold determined based of classification error in the data.

Abstract: A method for adjusting the tone scale reproduction of a color image composed of pixels provided in a plurality of color channels is based on generating a reference image from a combination of the color channels, whereby each spatial coordinate of the reference image is characterized by a reference image level. Channel averages of the color channel values of the pixels that correspond to the different valued reference image levels are generated. A channel tone scale transformation is formed by relating each channel average to its corresponding reference image level, and the channel tone scale transformation is utilized on a pixel by pixel basis in the respective channels of the digital color image to produce a processed digital color image having improved tone scale reproduction.

Abstract: A method for adjusting the color reproduction of a color image composed of pixels provided in a plurality of color channels is based on generating a reference image from a combination of the color channels, whereby each spatial coordinate of the reference image is characterized by a reference image level. Channel averages of the color channel values of the pixels that correspond to each of at least two different valued reference image levels are generated. Specific channel averages are obtained corresponding to a near white point and a near black point from the channel averages. The specific channel averages are utilized on a pixel by pixel basis for the respective channels of the digital color image to produce a processed digital color image having improved color reproduction.

Abstract: A retouching method for enhancing an appearance of a face located in a digital image involves acquiring a digital image containing one or more faces and detecting a location of facial feature points in the faces, where the facial feature points include points identifying salient features such as skin, eyes, eyebrows, nose, mouth, and hair. The location of the facial feature points are used to segment the face into different regions such as skin, eyes, eyebrows, nose, mouth, neck and hair regions. Facially relevant characteristics of the different regions are determined and, based on these facially relevant characteristics, an ensemble of enhancement filters are selected, each customized especially for a particular region, and the default parameters for the enhancement filters are selected. The enhancement filters are then executed on the particular regions, thereby producing an enhanced digital image from the digital image.

Abstract: In order to present digital images on different types of screens, and especially on low definition screens, the system provides a server that is adapted for receiving messages coming from at least one display device, and a table for recognizing the type of display device with which the server is communicating. The server performs a transformation for adapting the definition of the image that is transmitted to the type of display screen that is recognized.

Abstract: Creating a dental model from a series of images of an intra-oral object includes the steps of (a) capturing a series of images of an intra-oral object from a plurality of capture positions, where the object includes common surface features and a control target arranged with respect to the object to provide control features; (b) measuring the common features from the series of images of the object and the control features from the control target imaged with the images of the object; (c) analytically generating a 3-dimensional model of the object by photogrammetrically aligning the measurements of the control features, thereby reducing image errors due to the variability of the capture positions; and (d) adjusting the photogrammetrically aligned 3-dimensional model of the object by aligning the common features of the model to like features on the image of the object, thereby producing an aligned dental model from the series of images.

Abstract: A portable intra-oral capture and display system includes: (a) a handpiece elongated for insertion into an oral cavity, said handpiece including a light emitter on a distal end thereof for illuminating an object in the cavity and an image sensor for capturing an image of the object and generating an image signal therefrom; (b) a portable, hand-cradled base containing in a single integral enclosure a light source for generating light, electronics for processing the image for display, a display monitor for displaying the image, a storage for storing the image, thereby providing a stored image for subsequent review and access, and an interface for transferring the stored image to a peripheral device; and (c) an optical connection for transmitting the light from the base to the light emitter in the camera, and an electrical connection for communicating the image signal from the image sensor in the camera to the processor in the base.

Abstract: A digital image processing method detects facial features in a digital image. This method includes the steps of detecting iris pixels in the image, clustering the iris pixels, and selecting at least one of the following schemes 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 to identify eye positions is selected on the basis of the number of iris pixel clusters, and the facial features are located using the identified eye positions.

Abstract: In a method of improving a characteristic of an image according to its material content, where the image is comprised of image pixels, a belief map corresponding spatially to the image pixels is generated. The belief map includes belief values indicating the likelihood that respective pixels are representative of a particular material, such as flesh. An improvement parameter is generated from the belief map, and the improvement parameter is applied uniformly to the image pixels to improve the characteristic, such as the sharpness, of the image.

Abstract: A batch processing method for enhancing an appearance of a face located in a digital image, where the image is one of a large number of images that are being processed through a batch process, comprises the steps of: (a) providing a script file that identifies one or more original digital images that have been selected for enhancement, wherein the script file includes an instruction for the location of each original digital image; (b) using the instructions in the script file, acquiring an original digital image containing one or more faces; (c) detecting a location of facial feature points in the one or more faces, said facial feature points including points identifying salient features including one or more of skin, eyes, eyebrows, nose, mouth, and hair; (d) using the location of the facial feature points to segment the face into different regions, said different regions including one or more of skin, eyes, eyebrows, nose, mouth, neck and hair regions; (e) determining one or more facially relevant character

Abstract: A method for classification of image regions by probabilistic merging of a class probability map and a cluster probability map includes the steps of a) extracting one or more features from an input image composed of image pixels; b) performing unsupervised learning based on the extracted features to obtain a cluster probability map of the image pixels; c) performing supervised learning based on the extracted features to obtain a class probability map of the image pixels; and d) combining the cluster probability map from unsupervised learning and the class probability map from supervised learning to generate a modified class probability map to determine the semantic class of the image regions. In one embodiment the extracted features include color and textual features.

Abstract: A method for detecting objects in a digital image includes the steps of generating a first segmentation map of the digital image according to a non-object specific criterion, generating a second segmentation map of the digital image according to an object specific criterion, and detecting objects in the digital image using both the first and second segmentation maps. In a preferred embodiment of the invention, the non-object specific criterion is a color homogeneity criterion and the object specific criterion is an object specific color similarity, wherein the object specific color is skin color and the method further comprises the step of detecting red-eye in the detected skin color regions.

Abstract: In a method for determining the general semantic theme of a group of images, whereby each digitized image is identified as belonging to a specific group of images, one or more image feature measurements are extracted from each of the digitized images in an image group, and then used to produce an individual image confidence measure that an individual image belongs to one or more semantic classifications. Then, the individual image confidence measures for the images in the image group are used to produce an image group confidence measure that the image group belongs to one or more semantic classifications, and the image group confidence measure is used to decide whether the image group belongs to one or to none of the semantic classifications, whereby the selected semantic classification constitutes the general semantic theme of the group of images.

Abstract: A graphical user interface (GUI) allows a picture database user to enter metadata serving to annotate digital pictures to promote efficient picture database browsing. The annotation is permitted, not just for individual pictures, but for groups of pictures. The annotation information can be entered quickly, via a user-friendly interface (200, 204, 206), and can contain “social” information (via 116, 118 and 120) about groups of pictures (130–146), such as capture location, date and time, people or objects featured in groups of pictures, and events recorded by a group of pictures.

Abstract: A method for integrated retrieval and annotation of stored images involves running a user application in which text entered by a user is continuously monitored to isolate the context expressed by the text. The context is matched with metadata associated with the stored images, thereby providing one or more matched images, and the matched images are retrieved and displayed in proximity with the text. The context is then utilized to provide suggested annotations to the user for the matched images, together with the capability of selecting certain of the suggested annotations for subsequent association with the matched images. In a further extension, the method provides the user with the capability of inserting selected ones of the matched images into the text of the application, and further provides for automatically updating the metadata for the matched images.

Abstract: A novel multi-resolution block sampling based texture analysis/synthesis algorithm. A reference texture is assumed to be sample from a probability function. The synthesis of a similar, but distinctive, synthetic texture is handled in a process and by an apparatus that first estimates and then resamples the probability function. In order to achieve good and fast estimation of the probability function for a reference texture and in order to retain the texel structural information during the synthesis, a novel concept of block sampling and a corresponding novel texture synthesis scheme based on multi-resolution block sampling is employed. As a result of this novel approach, the computational complexity of the present invention is much lower than that of other approaches to the problem. In addition, for textures that exhibit a high degree of directionality, a process, which integrates estimation of dominant texture direction and the synthesis algorithm is employed to handle directional textures.

Abstract: A technique for producing a foreground mask from a digital image is based on receiving two digital images, wherein a first digital image is derived from a first original scene image including a foreground photographed against a background having arbitrary and unknown content matter, and a second digital image is derived from a second original scene image including substantially the same background but without the foreground. The second digital image is automatically aligned to the first digital image without user intervention to generate an aligned digital image including the background without the foreground. Then, using the first digital image and the aligned digital image, a foreground mask is produced relating to the spatial regions in the first digital image pertaining to the foreground, whereby the foreground mask is subsequently used to generate a composite digital image.