Abstract: A method for training a deep learning algorithm using N-dimensional data sets may be provided. Each data set comprises a plurality of N?1-dimensional data sets. The method comprises selecting a batch size and assembling an equally sized training batch. The samples are selected to be evenly distributed within said respective N-dimensional data sets. The method comprises also starting from a predetermined offset number, wherein the number of samples is equal to the selected batch size number, and feeding said training batches of N?1-dimensional samples into a deep learning algorithm for the training. Upon the training resulting in a learning rate that is below a predetermined level, selecting a different offset number for at least one of said N-dimensional data sets, and going back to the step of assembling. Upon the training resulting in a learning rate that is equal or higher than said predetermined level, the method stops.

Abstract: Navigation systems and methods for tracking physical objects near a target site during a surgical procedure. The navigation system comprises a robotic device and an instrument attached to the robotic device. A vision device is attached to the robotic device or the instrument and generates vision data sets. The vision data sets are captured from multiple perspectives of the physical object. A computing system associates a virtual object with the physical object based on one or more features of the physical object identifiable in the vision data sets. The virtual object at least partially defines a virtual boundary for the instrument.

Abstract: Provided is an image processing apparatus that can reduce degradation in image quality due to heat haze and the like. An input image memory 110 stores an input image group 200 and an input image 210. A time-series smoothed image memory 112 stores a time-series smoothed image 220 obtained by time series smoothing. A moving body removed image memory 113 stores a moving body removed image 230 that is a background image. A histogram analyzing unit 130 computes a differential of histograms of partial images for the input image 210 and the time-series smoothed image 220 or the moving body removed image 230, and calculates similarity information between the images. On the basis of the similarity information, a region dividing unit 140 divides the input image 210 into a moving body region, and a region other than the moving body region. An image correcting unit 150 performs image synthesis of the input image 210 or the time series-smoothed image 220, for each of the regions.

Abstract: The innovation discloses systems and methods of authenticating users using vein or blood vessel characteristics. The innovation retrieves, based on an authentication request, an authentication image associated with a user. The authentication image comprises a first predetermined point and a second predetermined point. The innovation projects the authentication image onto a body part of the user and reads a blood vessel from the body part. The user orients the blood vessel such that it corresponds to the predetermined points in the projected authentication image. The user is authenticated when the blood vessel appears to connect the predetermined points in the direction of the blood flow.

Abstract: Dual-energy absorptiometry is used to estimate intramuscular adipose tissue metrics and display results, preferably as related to normative data. The process involves deriving x-ray measurements for respective pixel positions related to a two-dimensional projection image of a body slice containing intramuscular adipose tissue as well as subcutaneous adipose tissue, at least some of the measurements being dual-energy x-ray measurements, processing the measurements to derive estimates of metrics related to the intramuscular adipose tissue in the slice, and using the resulting estimates. Processing the measurements includes an algorithm which places boundaries of regions, e.g., a large region and a smaller region. The regions are combined in an equation that is highly correlated with intramuscular adipose tissue measured by quantitative computed tomography in order to estimate intramuscular adipose tissue.

Abstract: An approach to joint acoustic and visual processing associates images with corresponding audio signals, for example, for the retrievals of images according to voice queries. A set of paired images and audio signals are processed without requiring transcription, segmentation, or annotation of either the images or the audio. This processing of the paired images and audio is used to determine parameters of an image processor and an audio processor, with the outputs of these processors being comparable to determine a similarity across acoustic and visual modalities. In some implementations, the image processor and the audio processor make use of deep neural networks. Further embodiments associate parts of images with corresponding parts of audio signals.

Abstract: Provided is a correction data generation method that includes acquiring captured image data by imaging an indicator that is related to a predetermined illness; plotting a real imaging data point that corresponds to the acquired captured image data in a predetermined color space that is associated with the predetermined illness in accordance with a color component of the data point; calculating a correction value for correcting the values of pixels that make up a captured image captured by an electronic endoscope based on the distance between the data point and a predetermined target point in the predetermined color space; and storing the calculated correction value.

Abstract: A method for pairing a first device with a second device includes receiving, by the first device, a dynamic graphic pattern having a shape that changes over time. The dynamic graphic pattern being associated with the second device for pairing with the second device. The first device recognizes the dynamic graphic pattern associated with the second device. The second device is paired if the dynamic graphic pattern associated with the second device is recognized.

Abstract: A work region evaluating system includes an imaging unit and a processing unit. The processing unit includes an image processing section that converts a three-dimensional image of a vehicle body component recorded by the imaging unit to three-dimensional image data, an extraction section that extracts work regions and reference regions respectively from both the three-dimensional image data and three-dimensional design data, an alignment section that aligns the three-dimensional image data with the three-dimensional design data with reference to the reference regions, and an evaluation section that evaluates a relation between the work region extracted from the three-dimensional image data and the work region extracted from the three-dimensional design data, based on the three-dimensional image data and the three-dimensional design data which are aligned with each other by the alignment section.

Abstract: An image processing device includes: a plurality of label data generation units which generate label data in which a predetermined label is assigned to each of a plurality of pixels in each of a plurality of divided images; a plurality of label integration information generation units which correspond to the respective label data generation units and generate label integration information representing association of labels included in the label data in order to integrate label data generated by a corresponding label data generation unit and label data generated by another label data generation unit; a plurality of label integration units which generate integrated label data in which respective pieces of label data corresponding to neighboring divided images are integrated; and a label integration processing control unit which distributes the label data to the respective label integration units such that computational loads to integrate the label data are equalized.

Abstract: According to an embodiment, an image processing apparatus includes a matching unit configured to perform stereo matching processing on two images obtained through imaging using two cameras, an error map creating unit configured to create an error map indicating a displacement amount of the two images in a direction orthogonal to a search line for the two images subjected to the stereo matching processing, and a parallelization parameter error determining unit configured to determine whether or not there is an error of rectification which parallelizes the two images, based on the error map.

Abstract: Devices, systems and methods are disclosed for performing image processing at a camera-level. For example, a camera service may run on top of a camera hardware abstraction layer (HAL) and may be configured to perform image processing such as applying a blurring algorithm, applying a color filter and/or other video effects. An application may pass metadata to the camera service via an application programming interface (API) and the camera service may use the metadata to determine parameters for the image processing. The camera service may apply the blurring algorithm for a first period of time before transitioning to unblurred image data over a second period of time.

Abstract: A system for estimating fractional flow reserve (FFR) includes a front end application to receive image frames from an imaging system to develop a model of a vasculature system based on an observed concentration time profile at locations within the model using contrast dye in the vasculature system and movement of the vasculature system. A graphics processing unit is configured to represent a computed concentration time profile in the vasculature system using a Lattice-Boltzmann Method (LBM) to generate a representation of the vasculature system. A dynamic controller tunes a velocity field based on a mismatch between the observed concentration time profile and the computed concentration time profile at the locations within the model to obtain a best estimate of the velocity field to perform a FFR measurement.

Abstract: A crossbar array, comprises a plurality of row lines, a plurality of column lines intersecting the plurality of row lines at a plurality of intersections, and a plurality of junctions coupled between the plurality of row lines and the plurality of column lines at a portion of the plurality of intersections. Each junction comprises a resistive memory element, and the junctions are positioned to calculate a matrix multiplication of a first matrix and a second matrix.

Abstract: The method and device of present disclosure relates providing content access permission to a user of the device. The device comprises an image capturing unit to scan eyeballs of the user trying to access the device. The scanning results in generation of a current scanned eyeball image. The device further matches the current scanned eyeball image with a previously scanned eyeball image of an authorized user and plurality of scanned eyeball images of plurality of other users. Based on the matching, the device determines the user as the authorized user of the device or a guest. In case of authorized user, the device provides a complete access of the device to the authorized user. However, in case of guest user, the device determines the age of the guest user and then provides the access of contents and functionalities of the device based on the age of the guest user.

Abstract: A method for object distance detection and focal positioning in relation thereto. The method comprising the steps of: (a) identifying (via a computing device) a desired distance among a plurality of designated sites on an object; (b) adjusting a focus (via an autofocus device) onto the plurality of designated sites; (c) calculating (via an image recognition module) the actual distance among the plurality of designated sites; (d) determining (via the image recognition module) if error exist between the actual distance and the desired distance; and (e) wherein (in no particular order) repeating the steps of (b), (c), and (d) until no substantial error exists between the actual distance and the desired distance.

Abstract: Systems and methods are disclosed for image signal processing. For example, methods may include receiving a first image from a first image sensor; receiving a second image from a second image sensor; determining an electronic rolling shutter correction mapping for the first image and the second image; determining a parallax correction mapping based on the first image and the second image for stitching the first image and the second image; determining a warp mapping based on the parallax correction mapping and the electronic rolling shutter correction mapping, wherein the warp mapping applies the electronic rolling shutter correction mapping after the parallax correction mapping; applying the warp mapping to image data based on the first image and the second image to obtain a composite image; and storing, displaying, or transmitting an output image that is based on the composite image.

Abstract: The present invention is a collation/retrieval system collating a product manufactured by or delivered from a producer or a distributor with a product to be collated comprising: a storage unit that stores an image feature of a predetermined collation area of the product determined in advance at a position relative to a reference section common in every product; a to-be-collated product feature extraction unit that receives an image of the product to be collated and detecting the reference section of the product from the received image to extract an image feature of the collation area determined by reference to the reference section; and a collation unit that collates the stored image feature with the image feature of the collation area of the product to be collated.

Abstract: The present disclosure describes a system and method to manage image file storage that includes a memory device to store instructions and at least one processing device to execute the instructions stored in the memory device to determine a blur indication or a burst characteristic for each of a plurality of files stored on a storage medium, automatically identify candidate image files to delete based at least in part on the blur indication or the burst characteristic, and delete at least some of the candidate image files based on receiving a delete indication.

Abstract: A method for determining the velocity of a moving fluid surface, which comprises the following steps S1 to S5: S1) taking a sequence of images of the moving fluid surface by at least one camera; S2) comparing a first image from the sequence with a second image from the sequence in order to distinguish moving patterns of the fluid surface from non-moving parts and to obtain a first processed image (im_1f) comprising the moving patterns; S3) comparing a third image from the sequence with a fourth image from the sequence in order to distinguish moving patterns of the fluid surface from non-moving parts and to obtain a second processed image (im_2f) comprising the moving patterns; S4) comparing the first and second processed images in order to determine the spatial displacements of the moving patterns; and S5) determining from the spatial displacements the velocity.