Abstract: An automatic drug compounder system may be provided with various components and capabilities for reconstituting a drug in a vial and providing the reconstituted drug to a receiving container. The system may include a camera for capturing images of the vial and processing circuitry for extracting information such as a lot number and an expiration date from the images. The system may rotate the vial while capturing the images to capture images of the entire vial. The processing circuitry may search a portion of the image for the lot number and expiration date, the portion based on stored information. The stored information may include a location, orientation, font size, or font color for printed information for a particular vial. The stored information may be retrieved based on a bar code read by the system.

Abstract: Disclosed herein are a point cloud data transmission method including encoding point cloud data, and transmitting a bitstream containing the point cloud data, and a point cloud data processing method including receiving a bitstream containing point cloud data, and decoding the point cloud data.

Abstract: Various surgical hubs are disclosed. A surgical hub is for use with a medical imaging device at a remote surgical site in a surgical procedure. The surgical hub comprises a circuit configured to: receive a livestream of the surgical site from the medical imaging device; capture an image frame of a surgical step of the surgical procedure from the livestream; derive information relevant to the surgical step from data extracted from the image frame; and overlay the information onto the livestream.

Abstract: The present disclosure discloses an image recognition method and system based on deep learning. The image recognition method trains a recognizing engine for high resolution images and a recognizing engine for low resolution image separately. The two recognizing engines generate two independent feature groups specifically for high resolution and low resolution images respectively. A categorizing engine categorizes a testing image to a high resolution mode or a low resolution mode, and then the testing image is recognized by the appropriate recognizing engine. Therefore, the present disclosure increases the accuracy of image recognition under various conditions.

Abstract: The present invention provides autoradiography methods and systems for imaging via the detection of alpha particles, beta particles, or other charged particles. Embodiments of the methods and systems provide high-resolution 3D imaging of the distribution of a radioactive probe, such as a radiopharmaceutical, on a tissue sample. Embodiments of the present methods and systems provide imaging of tissue samples by reconstruction of a 3D distribution of a source of particles, such as a radiopharmaceutical. Embodiments of the methods and systems provide tomographic methods including microtomography, macrotomography, cryomicrotomography and cryomacrotomography.

Abstract: An image processing method and a related device are provided to obtain a target image wherein texture of the obtained image is clearer, the image processing method includes: obtaining a visible light image and an infrared light image; obtaining first luminance information of the visible light image and second luminance information of the infrared light image; fusing the first luminance information and the second luminance information, to obtain a contrast fusion image; obtaining first texture information of the visible light image and second texture information of the infrared light image; fusing the first texture information, the second texture information, and the contrast fusion image, to obtain a texture fusion image; obtaining a color fusion image based on the visible light image and the infrared light image; and fusing the texture fusion image and the color fusion image, to obtain a target image.

Abstract: Provided is a tangible, non-transitory, machine readable medium storing instructions that when executed by the processor effectuates operations including: capturing visual readings to objects within an environment; capturing readings of wheel rotation; capturing readings of a driving surface; capturing distances to obstacles; determining displacement of the robotic device in two dimensions based on sensor readings of the driving surface; estimating, with the processor, a corrected position of the robotic device to replace a last known position of the robotic device; determining a most feasible element in an ensemble based on the visual readings; and determining a most feasible position of the robotic device as the corrected position based on the most feasible element in the ensemble and the visual readings.

Abstract: Methods, systems, devices and computer software/program code products enable generating reduced-noise image frames based on image frames received from a digital, camera pipeline; and enable efficient stereo image search between corresponding images generated by at least two cameras.

Abstract: A display device includes: a substrate including, in a plan view, a first area and a second area; a first sub-pixel disposed on the substrate, the first sub-pixel including an emission area disposed in the first area; a second sub-pixel disposed on the substrate, the second sub-pixel including an emission area disposed in the second area; a transmission area disposed on the substrate, the transmission area being adjacent to the second sub-pixel disposed in the second area; and a sensor disposed under the substrate, the photo sensor disposed in the second area. The emission area of the first sub-pixel has a first size and the emission area of the second sub-pixel has a second size different from the first size.

Abstract: An image processing device (500) according to the present invention is provided with: a visibility index computation means (501) which, upon receiving two or more images to be merged, computes, for each image to be merged, a visibility index, which is an index relating to the visibility of an object to be viewed in the image, on the basis of a contrast value of the image and the amount of noise included in the image, wherein the two or more images to be merged have different characteristics and have at least an overlap region; a merge ratio computation means (502) which computes an image merge ratio between the images to be merged, on the basis of the computed visibility indices; and an image merging means (503) which merges the images to be merged, on the basis of the computed merge ratio, to generate a merged image.

Abstract: An information processing apparatus (2000) includes a first analyzing unit (2020), a second analyzing unit (2040), and an estimating unit (2060). The first analyzing unit (2020) calculates a flow of a crowd in a capturing range of a fixed camera (10) using a first surveillance image (12). The second analyzing unit (2040) calculates a distribution of an attribute of objects in a capturing range of a moving camera (20) using a second surveillance image (22). The estimating unit (2060) estimates an attribute distribution for a range that is not included in the capturing range of the moving camera (20).

Abstract: A foldable display device is disclosed and has a first display region, a second display region, and a foldable region connecting the first display region and the second display region. The foldable display device includes a first biometric sensor disposed in the first display region and a second biometric sensor disposed in the second display region.

Abstract: An interframe registration and adaptive step size-based non-uniformity correction method for an infrared image, comprising: first calculating a normalized cross-power spectrum of n-th and (n?1)-th original infrared images with the non-uniformity, and then calculating a horizontal relative displacement and a vertical relative displacement of the n-th and (n?1)-th original infrared images with the non-uniformity; calculating a space variance and a time variance of each pixel of the n-th original infrared image with the non-uniformity, using the obtained space variance and time variance to calculate an adaptive iterative step size of each pixel of the n-th original infrared image with the non-uniformity, and using the iterative step size to update a gain correction coefficient and a bias correction coefficient; finally, performing non-uniformity correction on the pixel in an overlapping area of the n-th and (n?1)-th original infrared images with the non-uniformity.

Abstract: An information processing apparatus (2000) includes a first analyzing unit (2020), a second analyzing unit (2040), and an estimating unit (2060). The first analyzing unit (2020) calculates a flow of a crowd in a capturing range of a fixed camera (10) using a first surveillance image (12). The second analyzing unit (2040) calculates a distribution of an attribute of objects in a capturing range of a moving camera (20) using a second surveillance image (22). The estimating unit (2060) estimates an attribute distribution for a range that is not included in the capturing range of the moving camera (20).

Abstract: A data generation apparatus includes: an acquisition unit configured to acquire an image of an object to be inspected including a defect, and a region of the image that includes the defect; a correction unit configured to correct the region acquired by the acquisition unit by expanding an outer edge of the region so that the number of pixels included in the region is increased by a predetermined amount; and a generation unit configured to generate learning data by associating the region corrected by the correction unit with the image.

Abstract: The present disclosure provides a texture recognition method and apparatus thereof. The texture recognition method includes: acquiring a side texture image of a selected joint of an creature to be recognized; extracting side texture features in the side texture image; and recognizing a side texture of the selected joint based on the extracted side texture features.

Abstract: A method for constructing a sequencing template based on an image, a device, and a system. The image includes first, second, third and fourth images of one same field of view corresponding to base extensions of A, T/U, G, and C respectively; the first, second, third and fourth images respectively include images M1 and M2, images N1 and N2, images P1 and P2, and images Q1 and Q2; the method includes combining any two of the images M1, M2, N1, N2, P1, P2, Q1, and Q2to perform bright spot matching, and enabling such images to participate in the combination for at least one time to obtain a plurality of combined images including first coincident bright spots, and merging the first coincident bright spots on the plurality of combined images to obtain a bright spot set corresponding to the sequencing template.

Abstract: A computer-implemented method is presented for inferring passenger routes in a subway system. The method includes identifying, via an imaging device, a target passenger within the subway system, employing an exiting flow extractor to determine passenger exiting waves, employing an exiting wave identifier to mark an exiting wave of the passenger exiting waves including the target passenger, employing a supporting evidence backtracer to determine an entrance gate for each of the passengers in the marked exiting wave including the target passenger, determining a route probability for each of the passengers in the marked exiting wave including the target passenger via voting or distribution estimation processing, and employing a most probable route inferer to infer a route of the target passenger based on an aggregate route probability for all the passengers in the marked exiting wave.

Abstract: An information processing apparatus (2000) includes a first analyzing unit (2020), a second analyzing unit (2040), and an estimating unit (2060). The first analyzing unit (2020) calculates a flow of a crowd in a capturing range of a fixed camera (10) using a first surveillance image (12). The second analyzing unit (2040) calculates a distribution of an attribute of objects in a capturing range of a moving camera (20) using a second surveillance image (22). The estimating unit (2060) estimates an attribute distribution for a range that is not included in the capturing range of the moving camera (20).

Abstract: A target detection method and apparatus, a target detection device and a storage medium. The target detection method comprises: acquiring n types of detection frames which are determined by n different target detectors and which are related to a positioning target, wherein the n different target detectors may extract n different types of image features from the same image, and n is a positive integer equal to or greater than 2; obtaining an integrated detection frame on the basis of the n types of detection frames; each target detector extracting image features from an input image on the basis of the integrated detection frame to obtain n types of image features; performing image feature optimization on the basis of the n types of image features to obtain optimized image features; and obtaining an optimized detection frame according to the optimized image features so as to detect a target.