Abstract: An analysis and classification tool compares at least a portion of a captured image and a reference image of nominally the same scene. One of the captured and reference images is taken with flash and the other is taken without flash. The tool provides a measure of the difference in illumination between the captured image and the reference image. The tool compares the measure with a threshold and segments a foreground region from a background region based on the measure.

Abstract: A digital image acquisition system having no photographic film, such as a digital camera, has a flash unit for providing illumination during image capture and a red-eye filter for detecting a region within a captured image indicative of a red-eye phenomenon, the detection being based upon a comparison of the captured image and a reference image of nominally the same scene taken without flash. In the embodiment the reference image is a preview image of lower pixel resolution than the captured image, the filter matching the pixel resolutions of the captured and reference images by up-sampling the preview image and/or sub-sampling the captured image. The filter also aligns at least portions of the captured image and reference image prior to comparison to allow for, e.g. movement in the subject.

Abstract: A digital image acquisition system includes a portable apparatus for capturing digital images and a digital processing component for detecting, analyzing and informing the photographer regarding motion blur, and for reducing camera motion blur in an image captured by the apparatus. The digital processing component operates by comparing the image with at least one other image, for example a preview image, of nominally the same scene taken outside the exposure period of the main image. In one embodiment the digital processing component determines the degree of artifacts and whether to inform the user that the image is blurred by identifying at least one feature in a single preview image which is relatively less blurred than the corresponding feature in the main image.

Abstract: An analysis and classification tool compares at least a portion of a captured image and a reference image of nominally the same scene. One of the captured and reference images is taken with flash and the other is taken without flash. The tool provides a measure of the difference in illumination between the captured image and the reference image. The tool compares the measure with a threshold and categorizes the scene as outdoor or indoor based on the measure.

Abstract: A digital image acquisition system includes a portable apparatus for capturing digital images and a digital processing component for detecting, analyzing, invoking subsequent image captures and informing the photographer regarding motion blur, and for reducing camera motion blur in an image captured by the apparatus. The digital processing component operates by comparing the image with at least one other image, for example a preview image, of nominally the same scene taken outside the exposure period of the main image. In one embodiment the digital processing component identifies at least one feature in a single preview image which is relatively less blurred than the corresponding feature in the main image, calculates a point spread function (PSF) in respect of such feature, and initiates a subsequent capture if determined that the motion blur exceeds a certain threshold.

Abstract: A method of automatically determining a need to service a digital image acquisition system including a digital camera with a lens assembly includes analyzing pixels within one or more acquired digital images according to probability determinations that such pixels correspond to blemish artifacts. It is automatically determined whether a threshold distribution of blemish artifacts is present within one or more of the digital images. A need for service is indicated when at least the threshold distribution is determined to be present.

Abstract: A method of processing a digital image using face detection within the image achieves one or more desired image processing parameters. A group of pixels is identified that correspond to an image of a face within the digital image. Default values are determined of one or more parameters of at least some portion of the digital image. Values are adjusted of the one or more parameters within the digitally-detected image based upon an analysis of the digital image including the image of the face and the default values.

Abstract: A method of processing a digital image using face detection within the image achieves one or more desired image processing parameters. A group of pixels is identified that correspond to an image of a face within the digital image. Default values are determined of one or more parameters of at least some portion of the digital image. Values are adjusted of the one or more parameters within the digitally-detected image based upon an analysis of the digital image including the image of the face and the default values.

Abstract: Within a digital acquisition device, acquisition parameters of a digital image are perfected as part of an image capture process using face detection within said captured image to achieve one or more desired image acquisition parameters. Default values are determined of one or more image attributes of at least some portion of the digital image. Values of one or more camera acquisition parameters are determined. Groups of pixels are identified that correspond to an image of a face within the digitally-captured image. Corresponding image attributes to the groups of pixels are determined. One or more default image attribute values are compared with one or more captured image attribute values based upon analysis of the image of the face. Camera acquisition parameters are then adjusted corresponding to adjusting the image attribute values.

Abstract: A digital image acquisition system includes a portable apparatus for capturing digital images and a digital processing component for detecting, analyzing and informing the photographer regarding motion blur, and for reducing camera motion blur in an image captured by the apparatus. The digital processing component operates by comparing the image with at least one other image, for example a preview image, of nominally the same scene taken outside the exposure period of the main image. In one embodiment the digital processing component identifies at least one feature in a single preview image which is relatively less blurred than the corresponding feature in the main image, calculates a point spread function (PSF) in respect of such feature, and de-convolves the main image using the PSF.

Abstract: A processor-based system operating according to digitally-embedded programming instructions includes a face detection module for identifying face regions within digital images. A normalization module generates a normalized version of the face region. A face recognition module automatically extracts a set of face classifier parameter values from the normalized face region that are referred to as a faceprint. A workflow module automatically compares the extracted faceprint to a database of archived faceprints previously determined to correspond to known identities. The workflow module determines based on the comparing whether the new faceprint corresponds to any of the known identities, and associates the new faceprint and normalized face region with a new or known identity within a database. A database module serves to archive data corresponding to the new faceprint and its associated parent image according to the associating by the workflow module within one or more digital data storage media.

Abstract: A digital segmentation method and apparatus determines foreground and/or background within at least one portion of a captured image. The determining includes comparing a captured image to a pre-captured or post captured reference image of nominally the same scene. One of the images is taken with flash and the other without. The system can be implemented as part of a digital camera acquisition chain having effective computation complexity.

Abstract: A digital image acquisition system includes a portable apparatus for capturing digital images and a digital processing component for detecting, analyzing and informing the photographer regarding motion blur, and for reducing camera motion blur in an image captured by the apparatus. The digital processing component operates by comparing the image with at least one other image, for example a preview image, of nominally the same scene taken outside the exposure period of the main image. In one embodiment the digital processing component determines the degree of artifacts and whether to inform the user that the image is blurred by identifying at least one feature in a single preview image which is relatively less blurred than the corresponding feature in the main image.

Abstract: A digital image acquisition system includes a portable apparatus for capturing digital images and a digital processing component for detecting, analyzing, invoking subsequent image captures and informing the photographer regarding motion blur, and for reducing camera motion blur in an image captured by the apparatus. The digital processing component operates by comparing the image with at least one other image, for example a preview image, of nominally the same scene taken outside the exposure period of the main image. In one embodiment the digital processing component identifies at least one feature in a single preview image which is relatively less blurred than the corresponding feature in the main image, calculates a point spread function (PSF) in respect of such feature, and initiates a subsequent capture if determined that the motion blur exceeds a certain threshold.

Abstract: A digital image acquisition system includes a portable apparatus for capturing digital images and a digital processing component for detecting, analyzing and informing the photographer regarding motion blur, and for reducing camera motion blur in an image captured by the apparatus. The digital processing component operates by comparing the image with at least one other image, for example a preview image, of nominally the same scene taken outside the exposure period of the main image. In one embodiment the digital processing component identifies at least one feature in a single preview image which is relatively less blurred than the corresponding feature in the main image, calculates a point spread function (PSF) in respect of such feature, and de-convolves the main image using the PSF.

Abstract: A method of processing a digital image using face detection within the image achieves one or more desired image processing parameters. A group of pixels is identified that correspond to an image of a face within the digital image. Default values are determined of one or more parameters of at least some portion of the digital image. Values are adjusted of the one or more parameters within the digitally-detected image based upon an analysis of the digital image including the image of the face and the default values.

Abstract: A method for red-eye detection in an acquired digital image comprises acquiring a first image and analyzing the first acquired image to provide a plurality of characteristics indicative of image quality. The process then determines if one or more corrective processes can be beneficially applied to the first acquired image according to the characteristics. Any such corrective processes are then applied to the first acquired image. Red-eye defects are then detected in a second acquired image using the corrected first acquired image. Defect detection can comprise applying a chain of one or more red-eye filters to the first acquired image. In this case, prior to the detecting step, it is determined if the red-eye filter chain can be adapted in accordance with the plurality of characteristics; and the red-eye filter is adapted accordingly.

Abstract: A method of generating one or more new spatial and chromatic variation digital images uses an original digitally-acquired image which including a face or portions of a face. A group of pixels that correspond to a face within the original digitally-acquired image is identified. A portion of the original image is selected to include the group of pixels. Values of pixels of one or more new images based on the selected portion are automatically generated, or an option to generate them is provided, in a manner which always includes the face within the one or more new images. Such method may be implemented to automatically establish the correct orientation and color balance of an image. Such method can be implemented as an automated method or a semi automatic method to guide users in viewing, capturing or printing of images.

Abstract: A method of filtering a red-eye phenomenon from an acquired digital image including a multiplicity of pixels indicative of color, the pixels forming various shapes of the image, includes analyzing meta-data information, determining one or more regions within the digital image suspected as including red eye artifact, and determining, based at least in part on the meta-data analysis, whether the regions are actual red eye artifact. The meta-data information may include information describing conditions under which the image was acquired, captured and/or digitized, acquisition device-specific information, and/film information.

Abstract: Within a digital acquisition device, acquisition parameters of a digital image are perfected as part of an image capture process using face detection within said captured image to achieve one or more desired image acquisition parameters. Default values are determined of one or more image attributes of at least some portion of the digital image. Values of one or more camera acquisition parameters are determined. Groups of pixels are identified that correspond to an image of a face within the digitally-captured image. Corresponding image attributes to the groups of pixels are determined. One or more default image attribute values are compared with one or more captured image attribute values based upon analysis of the image of the face. Camera acquisition parameters are then adjusted corresponding to adjusting the image attribute values.