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 technique for processing a digital image uses face detection to achieve one or more desired image processing parameters. A group of pixels is identified that corresponds to a face image within the digital image. A skin tone is detected for the face image by determining one or more default color or tonal values, or combinations thereof, for the group of pixels. Values of one or more parameters are adjusted for the group of pixels that correspond to the face image based on the detected skin tone.

Abstract: A device is trained for face recognition. A first acquired digital image of a scene includes a face. Face image data is extracted and stored in a face image library along with an unique identifier. A second acquired digital image may or may not include the face of the same person as the face in the first acquired digital image. Face recognition is applied to extracted face data of the second digital image, and the face of the first digital image is displayed as a match to the face of the second digital image when the first and second images are determined to match or the second digital image or a face therein is identified with biometric data stored along with the first digital image when the faces in the first and second images are determined to match.

Abstract: A device is trained for face recognition. A first acquired digital image of a scene includes a face. Face image data is extracted and stored in a face image library along with an unique identifier. A second acquired digital image may or may not include the face of the same person as the face in the first acquired digital image. Face recognition is applied to extracted face data of the second digital image, and the face of the first digital image is displayed as a match to the face of the second digital image when the first and second images are determined to match or the second digital image or a face therein is identified with biometric data stored along with the first digital image when the faces in the first and second images are determined to match.

Abstract: A method for providing improved foreground/background separation in a digital image of a scene is disclosed. The method comprises providing a first map comprising one or more regions provisionally defined as one of foreground or background within the digital image; and providing a subject profile corresponding to a region of interest of the digital image. The provisionally defined regions are compared with the subject profile to determine if any of the regions intersect with the profile region. The definition of one or more of the regions in the map is changed based on the comparison.

Abstract: A method for providing improved foreground/background separation in a digital image of a scene is disclosed. The method comprises providing a first map comprising one or more regions provisionally defined as one of foreground or background within the digital image; and providing a subject profile corresponding to a region of interest of the digital image. The provisionally defined regions are compared with the subject profile to determine if any of the regions intersect with the profile region. The definition of one or more of the regions in the map is changed based on the comparison.

Abstract: A method and system for image recognition in a collection of digital images includes training image classifiers and retrieving a sub-set of images from the collection. For each image in the collection, any regions within the image that correspond to a face are identified. For each face region and any associated peripheral region, feature vectors are determined for each of the image classifiers. The feature vectors are stored in association with data relating to the associated face region. At least one reference region including a face to be recognized is/are selected from an image. At least one classifier on which said retrieval is to be based is/are selected from the image classifiers. A respective feature vector for each selected classifier is determined for the reference region. The sub-set of images is retrieved from within the image collection in accordance with the distance between the feature vectors determined for the reference region and the feature vectors for face regions of the image collection.

Abstract: A digital image processing technique gathers visual meta data using a reference image. A main image and one or more reference images are captured on a hand-held or otherwise portable or spatial or temporal performance-based image capture device. The reference images are analyzed based on predefined criteria in comparison to the main image. Based on said analyzing, supplemental meta data are created and added to the main image at a digital data storage location.

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 adjustable spatial and/or temporal compression of an image including a face includes identifying a group of pixels that correspond to a face within a digitally-acquired image. A first compression portion of the image including the group of pixels is determined. A second compression portion of the image other than the group of pixels is also determined. The first compression portion may be automatically compressed with higher-grade compression than the second compression portion to generate a compressed image including the face, or an option to provided the compressed image including the different grade compressions may be provided.

Abstract: A method for red-eye detection in an acquired digital image acquiring one or more preview or other reference images without a flash. Any red regions that exist within the one or more reference images are determined. A main image is acquired with a flash of approximately a same scene as the one or more reference images. The main image is analyzed to determine any candidate red eye defect regions that exist within the main image. Any red regions determined to exist within the one or more reference images are compared with any candidate red eye defect regions determined to exist within the main image. Any candidate red eye defect regions within the main image corresponding to red regions determined also to exist within the one or more reference images are removed as candidate red eye defect regions.

Abstract: Described herein are methods and devices of securing data. For example, a method of securing data comprises receiving, by a secure storage device, unsecure data from a source. The secure storage device is removably attached to the source. The method further comprises securing the unsecure data within the secure storage device by performing digital processing related to the unsecure data to create secure data. The secure storage device is responsive to the same protocol as an unsecure storage device and as a result the secure storage device is transparent to the source. The source responds to the secure storage device as if it were an unsecure storage device.

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 unsatisfactory scene is disqualified as an image acquisition control for a camera. An image is acquired. One or more eye regions are determined. The eye regions are analyzed to determine whether they are blinking, and if so, then the scene is disqualified as a candidate for a processed, permanent image while the eye is completing the blinking.

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 artefacts 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 image processing apparatus for tracking faces in an image stream iteratively receives an acquired image from the image stream potentially including one or more face regions. The acquired image is sub-sampled at a specified resolution to provide a sub-sampled image. An integral image is then calculated for a least a portion of the sub-sampled image. Fixed size face detection is applied to at least a portion of the integral image to provide a set of candidate face regions. Responsive to the set of candidate face regions produced and any previously detected candidate face regions, the resolution is adjusted for sub-sampling a subsequent acquired image.

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: An unsatisfactory scene is disqualified as an image acquisition control for a camera. An image is acquired. One or more mouth regions are determined. The mouth regions are analyzed to determined whether they are frowning, and if so, then the scene is disqualified as a candidate for a processed, permanent image while the mouth is completing the frowning.

Abstract: A method for red-eye detection in an acquired digital image includes acquiring a first image, and analyzing one or more partial face regions within the first image. One or more characteristics of the first image are determined. One or more corrective processes are identified including red eye correction that can be beneficially applied to the first image according to the one or more characteristics. The one or more corrective processes are applied to the first image.