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 method of automatically establishing the correct orientation of an image using facial information. This method is based on the exploitation of the inherent property of image recognition algorithms in general and face detection in particular, where the recognition is based on criteria that is highly orientation sensitive. By applying a detection algorithm to images in various orientations, or alternatively by rotating the classifiers, and comparing the number of successful faces that are detected in each orientation, one may conclude as to the most likely correct orientation. 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 digital camera that automatically corrects dust artifact regions within acquired images by compiling a dust map includes an optical system for acquiring an image with a corresponding dust calibration table for such optical system, including a lens assembly and an aperture stop, in which the corresponding dust calibration map can reside. A transformation between the dust map and the specific lens calibration table, enables the use for a single dust map in multiple instances of lenses and focal length, without the need to recalibrate the digital camera for each instance.

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 database of faceprint data corresponding to detected face regions within images acquired with an image acquisition device and digitally-embedded within one or more digital storage media includes image, identity and face recognition data components. The image data component include acquired digital image data including content data and unique identifiers corresponding to individual acquired digital images or face regions therein, or both. The identity data component includes an identification listing of known identities to which identified face regions detected within the image data have been determined to correspond. The face recognition data component includes, for an individual known identity, one or more identity tables corresponding to one or more identity entries, and one or more face class tables corresponding to one or more face class entries of the one or more identity tables.

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 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 method of automatically establishing the correct orientation of an image using facial information. This method is based on the exploitation of the inherent property of image recognition algorithms in general and face detection in particular, where the recognition is based on criteria that is highly orientation sensitive. By applying a detection algorithm to images in various orientations, or alternatively by rotating the classifiers, and comparing the number of successful faces that are detected in each orientation, one may conclude as to the most likely correct orientation. 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 modifying the viewing parameters of digital images using image feature detection for achieving desired parameters based on one or more sub-groups of pixels that correspond to one or more selected image features such as a face, body, pets, or a background region or a foreground region. Such methods may be used for animating still images, automating and streamlining application such as the creation of slide shows and screen savers of images containing selected image features. Two or more features such as a foreground region and a background region may be separated and independently processed.

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 extracts a set of face classifier parameter values from the normalized face region that are referred to as a faceprint. A workflow module 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 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 that is at least pose normalized. A face recognition module extracts a set of face classifier parameter values from the normalized face region that are referred to as a faceprint. A workflow module 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 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 extracts a set of face classifier parameter values from the normalized face region that are referred to as a faceprint. A workflow module 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. The archived faceprints are digitally organized and may be selectively recalled along with their associated parent images.

Abstract: A method of automatically correcting dust artifact within images acquired by a system including a digital camera includes determining that certain pixels correspond to dust artifact regions within a first digitally-acquired image. The dust artifact regions are associated with one or more extracted parameters relating to a variable optical system of the digital camera when the first image was acquired. An associated statistical dust map is formed including mapped dust regions based on known correspondence between effects on dust artifact data of values of extracted parameters. Pixels corresponding to correlated dust artifact regions within a second image acquired with said digital camera are corrected according to one or more different values of the extracted parameters relating to the variable optical system based on the associated statistical dust map.

Abstract: A method of automatically correcting dust artifact within images acquired by a system including a digital camera includes determining probabilities of dust artifact regions corresponding to pixels within a digitally-acquired image based at least in part on a pixel analysis of the region in view of predetermined characteristics indicative of the presence of a dust artifact region. The dust artifact regions are associated with one or more extracted parameters relating to the optical system when the image was acquired. A statistical dust map is formed including mapped dust regions based on the dust artifact determining and associating operations. Digital data is corrected corresponding to correlated dust artifact regions within the acquired image based on the associated statistical dust map.

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 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 one or more, or a chain of two 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 or red eye filter chain can be adapted in accordance with the characteristics. The red-eye filter may be adapted accordingly.

Abstract: A method automatically corrects dust artifact within images acquired by a system including a digital acquisition device including a lens assembly. Multiple original digital images are acquired with the digital acquisition device. Probabilities that certain pixels correspond to dust artifact regions within the images are determined based at least in part on a comparison of suspected dust artifact regions within two or more of the images. Probable dust artifact regions are associated with extracted parameter values relating to the lens assembly when the images were acquired. A statistical dust map is formed including mapped dust regions based on the determining and associating. Pixels corresponding to correlated dust artifact regions are corrected within further digitally-acquired images based on the associated statistical dust map.

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: 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.