Abstract: A control circuit having access to at least one high-energy image of a scene assesses that image to identify candidate obfuscaters as well as candidate obfuscated objects. This control circuit then processes information regarding the candidate objects to identify objects of interest. By one approach these objects of interest are deemed “of interest” as a function of their being obfuscated in a particular context. By one approach these teachings will accommodate identifying objects as being of interest as a function, at least in part, of the material composition of both the object as well as the visual obfuscater. These teachings also will accommodate peeling away background content/attenuation information in order to separate (and facilitate displaying) a given object in relative isolation from that background content.

Abstract: Elicited MRI signals are processed into MR image data in conjunction (a) with use of an initial spatially-selective RF tag pulse (tag-on) and (b) without use of an initial spatially-selective NMR RF tag pulse (tag-off) in respectively corresponding data acquisition subsequences. Multi-dimensional tag-on and tag-off data acquisition subsequences are used for each of plural time-to-inversion (TI) intervals without using an injected contrast agent. Acquired image data sets are subtracted for each TI interval to produce difference values as a function of time representing blood perfusion for the ROI that differentiates between normal, ischemic and infarct tissues.

Abstract: A view point is set inside a hollow organ, a clip plane crossing an internal cavity of the hollow organ is set in a position spaced apart in a visual line direction from the view point, a field of view from the view point is divided into a first field-of-view range in which the inside of the hollow organ is viewed and a second field-of-view range other than the first field-of-view range, a projection image is acquired using a template which is defined so that an inner wall surface of a large intestine is able to be drawn in the first field-of-view range, a projection image is acquired using a template which is defined so that a contact surface with the inner wall surface of the air region of the large intestine is able to be drawn in the second field-of-view range, and the projection images are connected.

Abstract: A structured light three-dimensional (3D) depth map based on content filtering is disclosed. In a particular embodiment, a method includes receiving, at a receiver device, image data that corresponds to a structured light image. The method further includes processing the image data to decode depth information based on a pattern of projected coded light. The depth information corresponds to a depth map. The method also includes performing one or more filtering operations on the image data. An output of the one or more filtering operations includes filtered image data. The method further includes performing a comparison of the depth information to the filtered image data and modifying the depth information based on the comparison to generate a modified depth map.

Abstract: A position information adding apparatus includes: a reference position setting unit which sets a plurality of reference positions for each of a plurality of pictures contained in digitalized video data; a region setting unit which sets a first position information adding region at a first position defined based on at least any of the plurality of reference positions and a second position information adding region at a second position different from the first position, for each of the plurality of pictures; and a position information embedding unit which embeds a first moving pattern which moves on the pictures in a first temporal period into the first position information adding region and a second moving pattern which moves on the pictures in a second temporal period into the second position information adding region.

Abstract: The recognition rate is improved and recognition errors are suppressed when recognizing magnetic ink characters. When the magnetic ink character 101 one character before the target character to which a magnetic recognition process is applied is not recognized, the character recognition unit 80 of a check reader 1 detects a different peak in a specific range before and after the position of the peak detected as the first peak of the one preceding magnetic ink character 101 in the signal waveform data, extracts character waveform data for the one preceding magnetic ink character 101 from the signal waveform data based on the position of the detected different peak, and applies the magnetic recognition process to the extracted character waveform data.

Abstract: Remote instruction and monitoring of health care may be facilitated by providing feedback to a local doctor performing the medical procedure while the local doctor is performing the medical procedure. Instructions for performing the medical procedure may be received from a remote doctor and transmitted to a local doctor. The local doctor may commence performing the medical procedure, and while the local doctor is performing the medical procedure, image or video of the medical procedure may be processed and compared to the instructions. For example, a first value of a parameter may be obtained from the image or video of the procedure and a second value of the parameter may be obtained from the instructions. Comparison data may be generated from the first value and the second value and presented to the local doctor and/or the remote doctor.

Abstract: SIFT features are selected from an input image. A SIFT procedure is applied to the input image to obtain candidate keypoints. For each candidate keypoint, there is calculation of a first Laplacian value (Lu) for pixels in an upper Scale Space and a second Laplacian value (Ll) for pixels in a lower Scale Space, based on the position of the candidate keypoint. A candidate keypoint is discarded if a Laplacian value Lc of the keypoint position is less than or equal to either of Lu or Ll. In the case that the candidate keypoint is not discarded, the candidate keypoint's Laplacian strength (Ls) is calculated, based on a relative change in Laplacian value from Lc to Lu and from Lc to Ll. One or more candidate keypoints are selected as SIFT features based on the corresponding Laplacian strength.

Abstract: Systems and methods are provided for image enhancement using self-examples in combination with external examples. In one embodiment, an image manipulation application receives an input image patch of an input image. The image manipulation application determines a first weight for an enhancement operation using self-examples and a second weight for an enhancement operation using external examples. The image manipulation application generates a first interim output image patch by applying the enhancement operation using self-examples to the input image patch and a second interim output image patch by applying the enhancement operation using external examples to the input image patch. The image manipulation application generates an output image patch by combining the first and second interim output image patches as modified using the first and second weights.

Abstract: Example methods, apparatus, systems to perform context-based image recognition for consumer market research are disclosed. Disclosed example methods include comparing a first subset of feature points in a first region of interest of a reference image with a first subset of feature points of a first image residing within a first region corresponding spatially to the first region of interest and located at a first location in the first image to determine a first match value. Disclosed example methods also include, in response to determining the first match value satisfies a first threshold, comparing a second subset of feature points in a second region of interest of the reference image with a second subset of the feature points of the first image residing within a second region of the first image corresponding spatially to the second region of interest to determine a second match value.

Abstract: A sensing module, such as a fingerprint sensing module, is disclosed. The sensing module includes a rigid substrate having a cutout, a flexible substrate attached to the rigid substrate, an image sensor including conductive traces formed on the flexible substrate, and a sensor integrated circuit that is connected to the conductive traces of the image sensor. The sensor integrated circuit is disposed in the cutout of the rigid substrate. The sensor integrated circuit can be fully enclosed in the cutout or disposed between the flexible substrate and the rigid substrate. The flexible substrate can also have a sensing side and a circuit side, where the conductive traces are formed on the circuit side and a finger is configured to be received from the sensing side. The conductive traces on the flexible substrate can also form a plurality of sensor gaps between respective image drive plates and image pickup plates.

Abstract: A first extracting unit extracts partial images from a learning image. A first calculator calculates a feature amount of the partial image. A retrieving unit retrieves objects included in the partial image, and gives, as a label, a vector to the feature amount. The vector represents relative positions between a first position in the partial image and each object included in the partial image. A voting unit generates a voting histogram for each partial image. A learning unit divides the feature amount of each partial image into clusters to reduce variation of the corresponding voting histogram, so as to learn a regression model representing a relationship between the feature amount of the partial image and the relative position of the object included in the partial image. A first predicting unit predicts, for each cluster, a representative label from the label given to the feature amount belonging to the cluster.

Abstract: Methods, systems, computer-readable media, and apparatuses for assigning a color class of a defined finite set of colors to at least one sub-region within a test image are presented. A plurality of sub-regions are identified within a test image. A first sub-region color value is determined for a selected first sub-region of the test image. Using the first sub-region color value and a plurality of zero-order probability distributions, a first color class of the defined finite set of colors is determined as a hypothesis color for the first sub-region. A second sub-region color value is determined for a selected second sub-region of the test image. Using the second sub-region color value and a conditional probability distribution conditioned on the hypothesis color for the first sub-region, a second color class of the defined set of colors is determined. The second color class is assigned to the second sub-region.

Abstract: An aerial image relates to a geographic area. The aerial image is analyzed to identify at least one traffic signal in the geographic area. Based at least in part on analyzing the aerial image, a timing prediction is determined for the at least one traffic signal.

Abstract: A computer implemented method for predicting preferences of an observer for two images, the method comprising the steps of: receiving the first image and an associated salience map indicating regions of the first image that are likely to be scrutinized by the observer; receiving a content masking map indicating differences between the first image and the second image that the observer is likely to be able to perceive; determining a number of preference measures; and processing the salience map and the content masking map to determine a distribution of a set of values of the preference measures predicting the preferences of the observer for the first image and the second image, the set of values of the preference measures having a number of degrees of freedom.

Abstract: A method and a system for rectifying a distorted fingerprint are provided. The method includes following steps. A feature of a distorted fingerprint is extracted, a reference distorted fingerprint whose feature is matched with the feature of the distorted fingerprint is searched for in a reference distorted fingerprint database, a dense distortion field of the reference distorted fingerprint is obtained in the reference distorted fingerprint database and the distorted fingerprint is rectified to a normal one according to the dense distortion field of the reference distorted fingerprint.

Abstract: Methods and systems described herein enable self-supervised road detection in images. The method includes receiving an image, segmenting the image into at least one fragment based at least in part on at least one pixel feature, determining, using a processor, a road likeness score for the at least one fragment based at least in part on a medial radius, and identifying roads based at least in part on the road likeness score.

Abstract: A computer-implemented technique for feature extraction includes obtaining an electronic image of an object and performing an edge detection algorithm on the electronic image. The technique further includes performing an edge pooling algorithm and sampling the electronic image edge patches, color patches and texture patches. A set of patches is selected from the edge patches, color patches and texture patches by selecting an (ith+1) patch to be within the set of patches based on a Euclidean distance from an ith patch of the set of patches for each of the set of edge patches, the set of color patches and the set of texture patches. A part selection algorithm and a part pooling algorithm is performed to obtain parts that are registered to the object.

Abstract: A system 100 for processing medical images, the system being arranged for obtaining a first medical image 102 and a second medical image 104, the first medical image and the second medical image being rigidly registered medical images of an anatomical structure, and the system comprising a displacement estimator 120 for establishing displacement vectors 122 for at least a first portion of the first medical image, the displacement vectors matching the first portion of the first medical image to a second portion of the second medical image, a deformation estimator 140 for, in dependence on the displacement vectors, establishing deformation values 142 for the first portion, the deformation values representing a deformation of the first portion with respect to the second portion, and a visualization generator 160 for generating visualization data 162 for, when being displayed on a display 180, establishing a multi-dimensional graph 182 comprising magnitudes of the displacement vectors as first variables 184 and t

Abstract: A method includes estimating structure models for a voxel(s) of a spectral image based on a noise model, fitting structure models to a 3D neighborhood about the voxel(s), selecting one of the structure models for the voxel(s) based on the fittings and predetermined model selection criteria, and de-noising the voxel(s) based on the selected structure model, producing a set of de-noised spectral images. Another method includes generating a virtual contrast enhanced intermediate image for each energy image of a set of spectral images corresponding to different energy ranges based on de-noised spectral images, decomposed de-noised spectral images, an iodine map, and a contrast enhancement factor; and generating final virtual contrast enhanced images by incorporating a simulated partial volume effect with the intermediate virtual contrast enhanced images.