Abstract: Handwriting verification methods and related computer systems, and handwriting-based user authentication methods and related computer systems are disclosed. A handwriting verification method comprises obtaining a handwriting test sample containing a plurality of available parameters, extracting geometric parameters, deriving geometric features comprising an x-position value and a y-position value for each of a plurality of feature points in the test sample, performing feature matching between geometric features of the test sample and a reference sample, determining a handwriting verification result based at least in part on the feature matching, and outputting the handwriting verification result. The geometric features may further comprise values derived from the geometric parameters, such as direction and curvature values. The handwriting verification result can be further based on a count of unlinked feature points.

Abstract: A process and apparatus for tracking a deceased body. The apparatus includes a processor and at least one remote computer system adapted to read and store a unique biometric input from a deceased body. The biometric input is catalogued with a unique identifier. Prior to cremation of a deceased body at a crematorium, the biometric input is scanned and matched to stored data to verify the identity of the deceased body. The deceased body is cremated in a retort furnace, processed in cremains processor and stored in a locking urn with a keepsake including the identifier such that the identity of the remains is shown.

Abstract: An electronic apparatus comprises a body, a human-machine interface device, a small-width biometrics sensor and a processing module. The human-machine interface device is disposed on the body. The small-width biometrics sensor is disposed on the body. The processing module, disposed on the body and electrically connected to the small-width biometrics sensor and the human-machine interface device, cooperates with the human-machine interface device and the small-width biometrics sensor to guide different physical portions of a finger of a user to directly contact or approach the small-width biometrics sensor according to indications of the human-machine interface device, so that the small-width biometrics sensor senses the finger to capture partial physical patterns of the finger. A guiding method of the electronic apparatus is also disclosed.

Abstract: Methods and apparatuses for authenticating a biometric scanner, such as area type finger print scanners, involves estimating unique intrinsic characteristics of the scanner (scanner pattern), that are permanent over time, and can identify a scanner even among scanners of the same manufacturer and model. Image processing and analysis are used to extract a scanner pattern from images acquired with the scanner. The scanner pattern is used to verify whether the scanner that acquired a particular image is the same as the scanner that acquired one or several images during enrollment of the biometric information. Authenticating the scanner can prevent subsequent security attacks using counterfeit biometric information on the scanner, or on the user authentication system.

Abstract: According to a fingerprint authentication method, fingerprint data is obtained through a fingerprint sensor, a degree of rotation of an electronic device including the fingerprint sensor when the fingerprint data is obtained is detected, a pattern of minutiae is extracted from the fingerprint data, a registration pattern for a registered fingerprint is rotated based on the degree of rotation, the pattern of minutiae is matched to the registration pattern, and the fingerprint data is authenticated on the basis of a match result.

Abstract: An apparatus and method based on image for detecting heart rate activity is provided. The method includes: obtaining a plurality of color images; based on a complexion target condition, defining a target region; performing color composition analysis on the target region to obtain red channel signal, green channel signal and blue channel signal, respectively; performing independent component analysis on separate red, green and blue channel signals to obtain separate first independent component signal, second independent component signal and third independent component signal; performing frequency domain transform, signal energy computation and signal optimization processes on separate first, second and third independent component signals to obtain a filter signal, comparing filter signal based on a pre-set condition to determine if target region belonging to a human, and performing a physiological information analysis.

Abstract: An apparatus for registering medical image data representing a tubular structure comprises a data processing unit for obtaining first medical image data representing the tubular structure and second medical image data representing the tubular structure, a region identification unit for identifying the tubular structure in the first medical image data, defining in the first medical image data a volumetric region of interest comprising the tubular structure along the length of the tubular structure and defining a subset of the first medical image data corresponding to the region of interest, and a registration unit for performing a registration of the subset of the first medical image data with at least some of the second medical image data, wherein the registration comprises at least one of a rigid registration and an affine registration.

Abstract: An embodiment of the invention relates to a method of visualization, wherein a 2D transformed image is generated based on 3D image data. A corresponding computation unit, a system including a computation unit and a displaying unit, a medical imaging device, and a computer program are also disclosed. The method of visualization of an embodiment includes receiving 3D image data representing at least a portion of a spine and a plurality of ribs; and generating a 2D transformed image based on the three-dimensional image data, the 2D transformed image representing the plurality of ribs and the portion of a spine in a straightened configuration, and the angle of rotation of at least one of the ribs around its long axis being selected from a plurality of angles. Selecting an angle of rotation from a plurality of angles allows selecting the perspective for viewing the ribs in the 2D transformed image.

Abstract: An image data processing apparatus comprises a data receiving unit for receiving image data to be segmented, and an atlas selection unit for accessing a plurality of atlas data sets and selecting a subset of the atlas data sets for use in segmenting the image data, wherein the atlas selection unit is configured to select the subset of atlas data sets in dependence on the positions of one or more anatomical landmarks comprised in the plurality of atlas data sets.

Abstract: The present invention is directed to a new joint estimation framework employing MAP estimation based on pixel-based latent variables for tissue types. The method combines the geometrical information described by latent MRF, statistical relation between tissue types and P-C coefficients, and Poisson noise models of PCD data, and makes possible the continuous Baysian estimation from detected photon counts. The proposed method has better accuracy and RMSE than the method using FBP and thresholding. The joint estimation framework has the potential to further improve the accuracy by introducing more information about tissues in human body, e.g., the location, size, and number of tissues, or limited variation of neighboring tissues, which will be easily formulated by pixel-based latent variables.

Abstract: According to one embodiment, an MRI apparatus includes a data acquiring part and a data processing part. The data acquiring part acquires first and second MR signals by applying at least one IR pulse under an application condition according to a relaxation time of a fluid. The first MR signals include MR signals, having negative values, from the fluid. The second MR signals include MR signals, having positive values, from the fluid. The data processing part generates first and second image data. The first image data depict the fluid as a lower signal region than that of a tissue. The second image data depict the fluid as a higher signal region than that of the tissue. The data processing part generates the first image data with a phase correction based on the second MR signals.

Abstract: There is provided a method of reducing noise in a medical image while maintaining structure characteristics within the medical image. The method of reducing noise in the medical image includes: a step of estimating the amount of noise at each pixel by using a look-up table that previously stores physical properties of an image capturing device; a step of calculating a structure direction and a signal coherence at each pixel; a step of performing anisotropic smoothing by using an anisotropic smoothing filter kernel that reflects the structure direction and the signal coherence; and a step of obtaining a structure direction and a signal coherence from an image on which the anisotropic smoothing is performed, obtaining an anisotropic smoothing filter kernel that reflects the obtained structure direction and the signal coherence, and performing filtering that reflects statistical properties of the estimated amount of noise.

Abstract: A method for co-registration of angiography and intravascular images is described in which intravascular images are in the form of a sequence of images obtained from an intravascular imaging device which is pulled back through a vessel. The method includes generating a three-dimensional reconstruction of the trajectory of the intravascular device within the vessel from two or more bi-dimensional angiography images of such vessel which have been obtained from different perspectives. The method also includes determining a first position of an element of the device within the 3D reconstruction of the trajectory and correlating the position of such element with a correspondent point in the reconstructed trajectory during pull back. Further, the method includes correlating each intravascular image of the sequence with a corresponding spatial position within at least one of the bi-dimensional angiography images. A corresponding system and computer program are also described.

Abstract: Data processing system for generating representations and analyses of cytometric information for:—loading one set of data including:—one image of two wells on a plate each having one cell in a predetermined biological condition, each image being acquired with a microscope;—features of each cell from each image;—processing loaded data for obtaining representations and analyses of the data, from:—Histogram in one dimension;—Scattergram in two-dimensions;—Density in two-dimensions;—Plate layout management;—Cell montage;—Field;—Plate heatmap;—Dose response with regrouping of replicates;—Statistics information percentage of cell in different gates;—zFactor calculation with regrouping of replicates;—List of well for selection and list of biological condition for selection;—Statistics export capability;—Ready to print layout capability on the selected well or biological condition or all wells and biological conditions.

Abstract: Systems and methods are provided for generating a model relating parameters generated via a first molecular imaging modality to parameters generated via a second molecular imaging modality. First and second feature extractors extract, from images of a region of interest obtained via respective first and second molecular imaging modalities, respective sets of parameters for respective first and second sets of locations. A mapping component associates respective locations of the first and second sets of locations according to their spatial relationship within the region of interest to produce a training set. Each example in the training set comprises a set of parameters associated with a location in the first set of locations and a set of parameters associated with a location in the second set. A modeling component generates a predictive model relating the parameters associated with the first modality with at least one parameter associated with the second modality.

Abstract: A necrotic cell region detection apparatus includes an image acquiring unit, a segmentation unit, a band separate unit, a feature value calculating unit, a luminance calculating unit, and a judging unit. The image acquiring unit acquires a cell image. The segmentation unit divides the cell image into multiple regions so that a local imaging properties. The band separate unit separates a low-band image and a high-band image. The judging unit forms a feature space composed of the texture feature value calculated by the feature value calculating unit and the luminance average value calculated by the luminance calculating unit, and judges a region formed by necrotic cell in the feature space.

Abstract: A method for identifying counterfeit coins, comprising receiving surface image data and edge image data of the coin at a processor. Identifying a plurality of defects using the processor. Comparing each of the plurality of defects to a database of known authentic coin image data defects to determine whether the coin is authentic.

Abstract: Provided is a method of detecting a defect of a pattern using vectorization to increase accuracy and efficiency in OPC modeling and OPC verification. The method includes acquiring a target layout image associated with a target pattern, acquiring a pattern image associated with a pattern formed on a substrate, extracting an edge image from the pattern image, producing a first vector form based on the target layout image, producing a second vector form based on the edge image, and comparing the first vector form with the second vector form.

Abstract: Acquired mask data of a defect portion is sent to a simulated repair circuit 300 to be simulated. The simulation of the acquired mask data 204 is returned to the mask inspection results 205 and thereafter sent to a wafer transfer simulator 400 along with a reference image at the corresponding portion. A wafer transfer image estimated by the wafer transfer simulator 400 is sent to a comparing circuit 301. When it is determined that there is a defect in the comparing circuit 301, the coordinates and the wafer transfer image which is a basis for the defect determination are stored as transfer image inspection results 206. The mask inspection results 205 and the transfer image inspection result 206 are then sent to the review device 500.

Abstract: A moving wafer imaging system processes wafer images to remove motion and focus blur by performing a blind deconvolution to determine an approximate point spread function. The approximate point spread function, estimated image noise and a Gaussian point spread function are used to compute a weighted point spread function. The weighted point spread function is used to filter out motion focus blur. Noise is then removed with a low-pass filter.

Abstract: A method for controlling the functional output of a verification tool upon receipt of a circuit description comprises searching for a predetermined base pattern in the circuit description. The method further comprises searching for predetermined sub-patterns that are assigned to the base pattern, in the circuit description. The method further comprises the validation of each found sub-pattern based on a predetermined rule to minimize the set of reported errors that based on verification of the circuit description.

Abstract: A system and method are provided for employing a unique optical roll scanning technique, scheme or process for detecting and identifying periodic surface defects associated with rolls usable in image production devices. An apparatus is provided for mounting the roll to implement an inspection technique that facilitates forming an image of a surface of the roll by rotating the roll through an entire cycle above a full width scanner device. The formed image of the surface of the scanned roll is filtered and analyzed particularly by applying a Fourier analysis technique, and/or by subjecting the filtered image data to a series of fast Fourier transforms (FFTs), potentially including 2D FFTs. The analysis process allows detected periodic defects in the formed image of the surface of the roll under analysis to be characterized by a magnitude of a response in a spatial frequency domain.

Abstract: A safety monitoring system for human-machine symbiosis is provided, including a spatial image capturing unit, an image recognition unit, a human-robot-interaction safety monitoring unit, and a process monitoring unit. The spatial image capturing unit, disposed in a working area, acquires at least two skeleton images. The image recognition unit generates at least two spatial gesture images corresponding to the at least two skeleton images, based on information of changes in position of the at least two skeleton images with respect to time. The human-robot-interaction safety monitoring unit generates a gesture distribution based on the at least two spatial gesture images and a safety distance. The process monitoring unit determines whether the gesture distribution meets a safety criterion.

Abstract: A method and apparatus for extracting surface representation from images and video data for segmenting image plane according to the surface connectivity, and identifying areas of images taken by a moving camera according to the object surfaces wherefrom the areas of images are taken, are disclosed. The invention discloses a method and apparatus comprising a plurality of processing modules for extracting from images in a video sequence the occluding contours delineating images into regions in accordance with the spatial connectivity of the correspondent visible surfaces, and diffeomorphism relations between areas of images taken from different perspective centers for identifying image areas of different frames as of the surface of same object, and specifying the fold contours of the surfaces that owns the contour, and thus producing the surface representations from video images taken from persistent objects by a moving camera.

Abstract: Blind image deblurring with a cascade architecture is described, for example, where photographs taken on a camera phone are deblurred in a process which revises blur estimates and estimates a blur function as a combined process. In various examples the estimates of the blur function are computed using first trained machine learning predictors arranged in a cascade architecture. In various examples a revised blur estimate is calculated at each level of the cascade using a latest deblurred version of a blurred image. In some examples the revised blur estimates are calculated using second trained machine learning predictors interleaved with the first trained machine learning predictors.

Abstract: Systems, devices, and methods for generating an image representation obtain a set of low-level features from an image; generate a high-dimensional generative representation of the low-level features; generate a lower-dimensional representation of the low-level features based on the high-dimensional generative representation of the low-level features; generate classifier scores based on classifiers and on one or more of the high-dimensional generative representation and the lower-dimensional representation, wherein each classifier uses the one or more of the high-dimensional generative representation and the lower-dimensional representation as an input, and wherein each classifier is associated with a respective label; and generate a combined representation for the image based on the classifier scores and the lower-dimensional representation.

Abstract: Software for supervised learning extracts a set of pixel-level features from each source image in collection of source images. Each of the source images is associated with a thumbnail created by an editor. The software also generates a collection of unique bounding boxes for each source image. And the software calculates a set of region-level features for each bounding box. Each region-level feature results from the aggregation of pixel values for one of the pixel-level features. The software learns a regression model, using the calculated region-level features and the thumbnail associated with the source image. Then the software chooses a thumbnail from a collection of unique bounding boxes in a new image, based on application of the regression model. The software uses a thumbnail received from an editor instead of the chosen thumbnail, if the chosen thumbnail is of insufficient quality as measured against a scoring threshold.

Abstract: Methods are disclosed relating to the production of camouflage that include steps such as harvesting a set of objects that have a diversity of color from the environment, placing the set of objects within a scene, capturing a set of images of the scene, adjusting color in the set of images, assembling a composite image, printing the composite image, making color adjustments and reprinting the composite image.

Abstract: The present invention provides a method for analyzing a digital image comprising a plurality of pixels representing a scene. The method comprising steps of obtaining pixel chromaticity information, providing, combinations each having a corresponding surface and a corresponding illuminant, performing a global scene surface-illuminant classification by determining hypothesis scores, accumulating hypothesis scores, thereby obtaining a global illuminant/surface statistic representing an estimate of a distribution of illuminants and/or surfaces in the scene as represented by the digital image. Other methods are also provided. Apparatuses for carrying out the methods are also provided.

Abstract: Image processing for productivity applications is provided. An image may be received by a computing device. The computing device may detect the edges comprising the received image and adjust the image based on a skew state of the detected edges. The computing device may then process the adjusted image to correct imbalances. The computing device may then assign an image classification to the processed image. The computing device may then adjust the processed image based on the assigned image classification.

Abstract: The present disclosure relates to an image processing device and method which can accurately reproduce a dynamic range of an image. A value on a vertical axis corresponding to a maximum white level is a digital value of the maximum white level (white 800%) which is assigned to a developed image, and is set as max_white_level_code_value which is one of characteristics information of the dynamic range and is transmitted. A value on the vertical axis corresponding to a white level is a digital value of a white level (white 100%) which is assigned to a developed image, and is set as white_level_code_value which is one of characteristics information of the dynamic range and is transmitted. The present disclosure is applicable to, for example, an image processing device.

Abstract: The present invention relates to an image processing device and method, which realize improvement in encoding efficiency for color difference signals and reduction in address calculations for memory access. In a case where a block size of orthogonal transform is 4×4, and a macroblock of luminance signals is configured of four 4×4 pixel blocks appended with 0 through 1, the four luminance signal blocks are corresponded with one color difference signal 4×4 block appended with C. At this time, there exist four motion vector information of mv0, mv1, mv2, and mv3, as to the four luminance signal blocks. The motion vector information mvc of the one color difference signal 4×4 block is calculated by averaging processing using these four motion vector information. The present invention can be applied to an image encoding device which performed encoding based on the H.264/AVC format, for example.

Abstract: When obtaining subband signals by performing multiresolution decomposition on image data using a broad-sense pinwheel framelet or a pinwheel wavelet frame, having a degree, that is a set of an approximate filter with no orientation and a plurality of detail filters with respective orientations, and acquiring processed image data by the subband signals in a decomposition phase of the multiresolution decomposition, or processed image data that has been reconstructed into an image by summing the subband signals in a synthesis phase of the multiresolution decomposition, the present invention performs attenuation or amplification of the subband signals in the decomposition phase of the multiresolution decomposition that correspond to at least one of the filters.

Abstract: An device, method and program may properly perform gamut conversion of content and be applied to a gamut conversion device. A restoration conversion state confirming unit performs confirmation such as gamut conversion state of image data read out from an optical disc and the existence or not of restoration metadata. An information exchange unit communicates with an output device via a communication unit and performs information exchange such as the existence or not of restoration processing functionality and gamut conversion functionality and the like. A determining unit determines whether or not restoration processing is performed with a playing device based on information obtained by the restoration conversion state confirming unit and the information exchange unit. Similarly, the determining unit determines whether or not to perform gamut conversion processing with the playing device based on information obtained by the restoration conversion state confirming unit and the information exchange unit.

Abstract: A character recognition method may include at least the following steps. A location step may include acquiring an image and locating a character region of the image. The character region may include a character and a local background. The method may further include a background judgment step for determining whether the local background is a complex background; a determination step for determining a color of the character if the local background is a complex background; a construction step for constructing a mask for the character by combining the color of the character and a character region; and a first recognition step for extracting the character from the character region by using the mask, recognizing the character, and outputting the recognition result. A character recognition device is further provided.

Abstract: In accordance with an example embodiment a method, apparatus and computer program product are provided. The method comprise assigning weights to at least one first feature and at least one second feature. The at least one first feature may be associated with a first image and the at least one second feature may be associated with a second image. The weights are assigned based on a distance of the at least one first feature and the at least one second feature from a central portion of the corresponding one of the first image and the second image. The method further includes registering the first image and the second image based at least on the assigned weights to determine transforms between the first image and the second image. The first image and the second image may be based on the determined transform.

Abstract: Methods, systems, and computer program products for parsing objects in a video are provided herein. A method includes producing a plurality of versions of an image of an object derived from a video input, wherein each version has a different resolution of said image of said object; computing an appearance score at each of a plurality of regions on the lowest resolution version of said plurality of versions of said image for at least one attribute for said object, wherein said appearance score denotes a probability of the at least one attribute appearing in the region; determining a configuration of the at least one attribute in the lowest resolution version based on at least the appearance score in each of the plurality of regions in the lowest resolution version; and displaying said configuration.

Abstract: A pattern processing apparatus includes an acquisition unit, an adjacent element identification unit, a connection unit, and an assigning unit. The acquisition unit acquires a pattern image in which a plurality of pattern elements are arrayed in a grid, together with coordinate information of the pattern elements. The adjacent element identification unit identifies, for each of the pattern elements thus acquired, adjacent elements, in at least two directions, each having the shortest distance to the each of the pattern elements. The distances between the each of the pattern elements and other pattern elements are calculated using the coordinate information. The connection unit connects and groups, as a connected component, the pattern elements that are adjacent to one another. The assigning unit assigns position information in the array in order from the pattern element which is a starting point, among the pattern elements included in the connected component, according to a predetermined regularity.

Abstract: A method, non-transitory computer readable medium and character recognition device for character recognition includes a character recognition device for receiving an image representing a character comprising one or more strokes. A set of first parameters associated with each of the one or more first strokes is determined. Each of the one or more first strokes is compared with the associated set of first parameters with a plurality of stored sets of second parameters, where each of the plurality of stored second strokes is associated with a stored set of second parameters. A second stroke is identified from among the plurality of stored second strokes corresponding to each of the one or more first strokes based on the comparison. The character is identified based on the identified one or more second strokes.

Abstract: Interactive drawing recognition is described using status determination. In one example, a computer system status is determined and then used to determine a type of drawing. A user drawing is observed and a library of drawing templates associated with the determined drawing type is accessed. The observed drawing is compared to the drawing templates to identify the observed drawing, and attributes are assigned to the identified drawing.

Abstract: This shape data generation method include: setting an input shape that has a simple shape that has a same topology as the target shape for a target shape that is a shape of a transformation target identified from image data; identifying first vertices that satisfy a predetermined condition including a first condition that a normal line of a certain vertex of the plural vertices crosses with the target shape, among plural vertices of the input shape; transforming the input shape so that a first vertex is moved in a direction of a normal line of the first vertex by a first distance that is shorter than a distance up to the target shape; and performing the identifying and the transforming a predetermined number of times while changing the input shape after the transforming as the input shape to be processed.

Abstract: In techniques for adaptive denoising with internal and external patches, example image patches taken from example images are grouped into partitions of similar patches, and a partition center patch is determined for each of the partitions. An image denoising technique is applied to image patches of a noisy image to generate modified image patches, and a closest partition center patch to each of the modified image patches is determined. The image patches of the noisy image are then classified as either a common patch or a complex patch of the noisy image, where an image patch is classified based on a distance between the corresponding modified image patch and the closest partition center patch. A denoising operator can be applied to an image patch based on the classification, such as applying respective denoising operators to denoise the image patches that are classified as the common patches of the noisy image.

Abstract: A system for contextualizing noisy samples by substantially minimizing noise induced variance may include a memory, an interface, and a processor. The memory is operative to store exemplars. The processor is operative to receive, via the interface, a sample which includes exemplar content corresponding to one of the exemplars, and noise. Variance induced by the noise may differentiate the sample from one or more of the exemplars. The processor may generalize the sample and the exemplars in order to substantially minimize the variance. The processor may compare the generalized sample to the generalized exemplars to identify the exemplar corresponding to the exemplar content of the sample. The processor may contextualize the sample based on a document type of the identified exemplar. The processor may present the contextualized sample to a user to facilitate interpretation thereof, and in response thereto, receive data representative of a user determination associated with the noise.

Abstract: A media decoding method based on cloud computing and decoder thereof are provided by embodiments of the present invention, which are easy to use and applicable to a media of any form, and its requirement for computer resource is low. The method includes: extracting representing features from a media code stream to be decoded; searching in the cloud for a media object which has similar representing features with the media code stream to be decoded by using a feature matching method and the representing features extracted; filling, replacing and improving parts or segments of the media code stream to be decoded with whole or parts of the media object.

Abstract: A system for document processing including decomposing an image of a document into at least one data entry region sub-image, providing the data entry region sub-image to a data entry clerk available for processing the data entry region sub-image, receiving from the data entry clerk a data entry value associated with the data entry region sub-image, and validating the data entry value.

Abstract: Various apparatuses and methods are disclosed for processing texture data compressed with a first compression algorithm and texture data compressed with a second compression algorithm. A processing system may be used to determine whether the compressed texture data is compressed with the first or second compression algorithm, and process the compressed texture data using a decompression algorithm corresponding to the compression algorithm used to compress the texture date.

Abstract: An image encoding apparatus and method and an image decoding apparatus and method are disclosed. The image encoding method may include extracting a ROI from an input image, determining a compression rate of a remaining region excluding the ROI of the image based on a network state between the image transmitting apparatus and the image receiving apparatus, and encoding the remaining region based on the compression rate.

Abstract: A coding and decoding method for images or videos is provided by embodiments of the present invention to improve coding and decoding efficiency. The method includes: establishing a visual dictionary, wherein, the visual dictionary includes one or more visual words; extracting features from a specific object in an image; determining whether there is a visual word in the visual dictionary matching the specific object by using a feature matching method; obtaining the index of the visual word matched and a geometric relationship between the specific object and the visual word matched, wherein, the geometric relationship is represented by a project parameter; entropy coding the index of the visual word matched and the project parameter instead of entropy coding the specific object.

Abstract: A method of removing noise of an image signal includes receiving a first frame and a second frame, generating a spatial filtering frame by performing spatial filtering on the second frame, generating a temporal filtering frame by performing temporal filtering on the first frame, and generating a second filtering frame, using the temporal filtering frame, the spatial filtering frame, and the second frame.

Abstract: Techniques are disclosed for dynamic digital image compositing using a digital image template. A request is received to generate a composite digital image at a user-specified resolution based on a master digital image. Each of a plurality of digital image templates includes image data representing a different, particular resolution of the master digital image. The digital image templates can be stored in a common file with the master digital image. One of the digital image templates associated with a resolution that is at least as high as and closest to the user-specified resolution is selected for compositing. Composite image data is then generated based on the selected digital image template. Next, the composite image is rendered based on the composite image data and scaled to the user-specified resolution.