Abstract: A display control apparatus performs overlapping display of a highlight image against a notification object that is visually recognized through a picture projection plane of a virtual image display apparatus used by a driver of a vehicle such that the highlight image represents the notification object. A target information acquisition section acquires target information including at least a position and a size of the notification object. A display execution section displays a first highlight image and a second highlight image in a display form capable of identifying each of the first highlight image and the second highlight image based on target information acquired by the target information acquisition section. The first highlight image corresponds to a size of the notification object, while the second highlight image results from enlarging the first highlight image at a predetermined magnification percentage.

Abstract: An image processing apparatus includes an exaggeration unit configured to perform on an original image including a hand-drawn element an exaggeration process that expands the hand-drawn element to generate an exaggerated image; and a reduction unit configured to reduce the exaggerated image to generate a reduced image of a predetermined size smaller than a size of the original image.

Abstract: At least some embodiments of the present disclosure feature systems and methods for assessing the impact of visual features within a region of a scene. With the input of a visual representation of a scene and at least one selected region within the scene, the system applies a visual attention model to the visual representation to determine visual conspicuity of the at least one selected region. The system computes feature-related data associated with a plurality of features of the at least one selected region. Based on the visual conspicuity and the feature-related data, the system assesses an impact that at least one of the features within the at least one selected region have on the visual conspicuity.

Abstract: Comparing extracted card data from a continuous scan comprises receiving, by one or more computing devices, a digital scan of a card; obtaining a plurality of images of the card from the digital scan of the physical card; performing an optical character recognition algorithm on each of the plurality of images; comparing results of the application of the optical character recognition algorithm for each of the plurality of images; determining if a configured threshold of the results for each of the plurality of images match each other; and verifying the results when the results for each of the plurality of images match each other. Threshold confidence level for the extracted card data can be employed to determine the accuracy of the extraction. Data is further extracted from blended images and three-dimensional models of the card. Embossed text and holograms in the images may be used to prevent fraud.

Abstract: A computed tomography (CT) apparatus includes a reconstruction unit which reconstructs a first CT image corresponding to a field of view (FOV) by using a first sinogram acquired by a CT scan of an object; and a correction unit which acquires a second sinogram by performing forward projection on the first CT image and acquires a second CT image by using the second sinogram and a third sinogram representing a portion of the object that is not included in the FOV. Thus, the CT apparatus reduces generation of image errors to thereby provide a high-quality reconstructed CT image.

Abstract: A system for detecting clouds and cloud shadows is described. In one approach, clouds and cloud shadows within a remote sensing image are detected through a three step process. In the first stage a high-precision low-recall classifier is used to identify cloud seed pixels within the image. In the second stage, a low-precision high-recall classifier is used to identify potential cloud pixels within the image. Additionally, in the second stage, the cloud seed pixels are grown into the potential cloud pixels to identify clusters of pixels which have a high likelihood of representing clouds. In the third stage, a geometric technique is used to determine pixels which likely represent shadows cast by the clouds identified in the second stage. The clouds identified in the second stage and the shadows identified in the third stage are then exported as a cloud mask and shadow mask of the remote sensing image.

Abstract: Presented herein are efficient and reliable systems and methods for calculating and extracting three-dimensional central axes of bones of animal subjects—for example, animal subjects scanned by in vivo or ex vivo microCT platforms—to capture both the general and localized tangential directions of the bone, along with its shape, form, curvature, and orientation. With bone detection and segmentation algorithms, the skeletal bones of animal subjects scanned by CT or microCT scanners can be detected, segmented, and visualized. Three dimensional central axes determined using these methods provide important information about the skeletal bones.

Abstract: Various embodiments may increase scalability of image representations stored in a database for use in image matching and retrieval. For example, a system providing image matching can obtain images of a number of inventory items, extract features from each image using a feature extraction algorithm, and transform the same into their feature descriptor representations. These feature descriptor representations can be subsequently stored and used to compare against query images submitted by users. Though the size of each feature descriptor representation isn't particularly large, the total number of these descriptors requires a substantial amount of storage space. Accordingly, feature descriptor representations are compressed to minimize storage and, in one example, machine learning can be used to compensate for information lost as a result of the compression.

Abstract: A method, apparatus, and program product evaluate fracture abundance in a subsurface formation by modeling a fracture network in a three-dimensional volume using geometric primitives. A fracture abundance parameter, e.g., a P32 fracture density, may be determined in part based upon the combined areas of the primitives with cells of a three-dimensional grid.

Abstract: The invention relates to method of classifying an object (10) in an image (9), the method comprising the steps of: defining an image area (11) located within the object (10) in the image (9), decomposing the image area (11) into an array of subareas (13), defining an array of aggregated pixel values by calculating, for each of the subareas (13), an aggregated pixel value of the respective subarea (13), calculating a gradient array depending on differences between the aggregated pixel values of adjacent subareas (13), analyzing the gradient array, identifying, depending on a result of the analyzing step, the object (10) as belonging to a class of a predefined set of classes. Furthermore, the invention relates to a device (4) for analyzing an object (10) contained in an image (9) and to a driver assistance system as well as to a vehicle (1) containing such a device (4).

Abstract: Systems, methods, and non-transitory computer readable media are described herein to facilitate generation of high-resolution two-dimensional projection images of an object having minimal artifacts from three-dimensional computed tomography volumes. Direct or iterative image reconstruction techniques can be used in concert with binning to identify and select measurement data subject to a criterion and resampling of the initial volumetric dataset to generate the high-resolution, two-dimensional projection images of at least a portion of the object.

Abstract: Automatic nuclear segmentation. In an embodiment, a plurality of superpixels are determined in a digital image. For each of the superpixels, any superpixels located within a search radius from the superpixel are identified, and, for each unique local combination between the superpixel and any identified superpixels located within the search radius from the superpixel, a local score for the local combination is determined. One of a plurality of global sets of local combinations with an optimum global score is identified based on the determined local scores.

Abstract: An optical tracking system includes a marker part, an image forming part, and a processing part. The marker part includes a pattern having particular information and a first lens. First and second image forming parts include second and third lenses and first and second image forming units. The processing part determines the posture of the marker part from a first coordinate conversion formula between a coordinate on the pattern surface of a pattern and first pixel coordinate on a first image of the pattern, and a second coordinate conversion formula between a coordinate on the pattern surface of the pattern and second pixel coordinate on a second image of the pattern, the second coordinate conversion formula including the rotation conversion between the first pixel coordinate and the second pixel coordinate and tracks the marker part by using the posture of the marker part.

Abstract: Three-dimensional image data of an imaged object, such as the bone structure of a patient, comprise first and second rigid parts movably connected to each other, in a first state of position and orientation. Sub-regions within the three-dimensional image data are divided into at least first image data and second image data. A set of two-dimensional projection images of the imaged object are taken from first and second different projection directions, while the first and the second rigid parts are in a second state of position and orientation. A processing device registers the first image data with the set of two-dimensional projection images and separately registers the second image data with the set of two-dimensional projection images to obtain first and second registration information, respectively, which is used to determine the position and orientation of the first and second rigid parts in the second state.

Abstract: When recognizing leads by processing an image captured by a camera of a component provided with a single row or multiple rows of leads of the same size and shape at a regular pitch, waveform analysis of a change pattern of brightness (pixel value) along multiple lines set in a vertical, a horizontal, or a diagonal direction of the image is performed so as to identify a region in which the brightness changes cyclically as a lead recognition target region in which there is a possibility of a lead existing. Then, image recognition of leads is performed in the lead recognition target region.

Abstract: A method for determining a spatial parameter for an object displayed on a device includes determining a first pixel coordinate corresponding to a first point of an image of the object and a second pixel coordinate corresponding to a second point of an image of the object displayed on the device, determining an image distance between the first pixel coordinate and the second pixel coordinate, and determining a spatial parameter for the object based on a distance between an imaging element of the device and the object, and a focal length of a lens of the imaging element for photographing the object. According to the technical solution of the present disclosure, the real size of the photographed object can be quantized based on the image, without having to illustrating the real size of the photographed object in contrast with a reference object placed in the image, thereby improving the user experience.

Abstract: An apparatus and corresponding method are provided to match images and include assigning depth candidate values to a pixel in a first image, and reassigning third depth candidate values to a first pixel in the first image based on first depth candidate values assigned to the first pixel and second depth candidate values assigned to a second pixel adjacent to the first pixel. The apparatus and method also include determining one of the third depth candidate values to be a depth value of the first pixel, and matching the first pixel and a third pixel in a second image corresponding to the determined depth value of the first pixel.

Abstract: A method for providing real time service of huge and high quality digital image on internet is disclosed, wherein data relevant to a general life such as a general photo, an advertising leaflet, and a pamphlet and professional image data exhibited in an art gallery, exhibition grounds, a pavilion are made into huge and high quality digital image or scanned and photographed to be digital, thereby processing real time service as an interactive browsing form. In the present invention, data are directly made, edited, constructed, and uploaded on internet, thereby providing various additional information with image through hyperlink and processing high quality digital image service on network without speed delay for huge image.

Abstract: Apparatus, methods, and other embodiments associated with image processing operations are disclosed that provide image contrast enhancement. According to one embodiment, an apparatus includes histogram stretching logic to generate a stretched histogram. The stretched histogram is generated by compressing an enlarging a contrast of brightness bins of an equalized histogram of brightness component values formed from a previous input frame of image pixel data. Flat region detection logic classifies pixels of the previous input frame of image pixel data as being flat pixels or non-flat pixels, and counts a number of the flat pixels. Noise detection logic classifies the flat pixels as being noisy pixels or non-noisy pixels, and counts a number of the noisy pixels. The number of noisy pixels and characteristics of the stretched histogram are used to enhance the contrast of a current input frame of image pixel data.

Abstract: A system that provides an improved way of scheduling a plurality of imaging tasks in a medical imaging system is disclosed. The system enables a user (i.e. a technician or medical expert) to group different imaging tasks and executes them simultaneously to significantly reduce scan time. These imaging tasks are of different types or are related to different imaging techniques. If different imaging tasks need to be performed substantially at the same location and have substantially same scan time then they can be scheduled simultaneously so that overall scan time can be reduced.