Abstract: A method for operating an arrival notification system at a location includes receiving a request to generate a notification from an arrival notification system. The method also includes receiving, in response to the request, a token. The method further includes enabling an output from a component of the arrival notification system when the token is validated.

Abstract: A method includes, responsive to receiving a shortcode from a client computing device, identifying, by a processing device based on the shortcode, computer-executable instructions and one or more geographical locations. The method further includes causing, based on the computer-executable instructions and the one or more geographical locations, the client computing device to generate an order request form filled with the one or more geographical locations received from the processing device based on the shortcode without user intervention and without user input of the one or more geographical locations. The method includes, responsive to receiving the order request form filled with the one or more geographical locations from the client computing device, transmitting, to a vehicle computing device, an order request to dispatch a transportation vehicle associated with the vehicle computing device to provide a transportation service to a user of the client computing device based on the order request form.

Abstract: Systems and methods are provided for managing subjective probability bets, the method comprising: receiving a set of bets; calculating one or more possible outcomes of a competition; for each possible outcome, determining whether each of the bets would be a winning bet or a losing bet; performing an iterative bet analysis procedure comprising: calculating a payable amount, calculating a payout amount, and determining whether the sum of the payable amount and a system threshold (indicating a maximum amount allowed to be paid out beyond the payable amount for the possible outcome) is greater than or equal to the payout amount; if it is determined that said sum is greater than or equal to the payout amount, assigning the outcome a pass value, and if it is determined that said sum is not greater than or equal to the payout amount, assigning the outcome a fail value.

Abstract: An image processing method comprising acquiring a plurality of pixel rows of an image according to a rectangular pixel region, and storing the plurality of pixel rows as blocks in a plurality of line buffers. A pixel row is stored as a block in a storage space of the plurality of line buffers, and a number of bits of the block in a line buffer is smaller than a number of pixel columns of the image.

Abstract: An image processing method for segmenting an image, the method comprising: receiving first image; producing a second image from said first image, wherein said second image is a lower resolution representation of said first image; processing said first image with a first processing stage to produce a first feature map; processing said second image with a second processing stage to produce a second feature map; and combining the first feature map with the second feature map to produce a semantic segmented image; wherein the first processing stage comprises a first neural network comprising at least one separable convolution module configured to perform separable convolution and said second processing stage comprises a second neural network comprising at least one separable convolution module configured to perform separable convolution; the number of layers in the first neural network being smaller than the number of layers in the second neural network.

Abstract: The present disclosure generally relates to machine vision systems, illumination sources for use in machine vision systems, and components for use in the illumination sources. More specifically, the present disclosure relates to machine vision systems incorporating multi-function illumination sources, multi-function illumination sources, and components for use in multi-function illumination sources.

Abstract: Disclosed is a hidden data removal method based on an autoregressive generative model which is performed by a computer device. The hidden data removal method includes receiving a source image, randomly selecting a target pixel from the source image, and inputting the source image and an identifier of the target pixel to an autoregressive generative model and restoring the target pixel from the source image. The source image is an image in which steganography-based data is hidden, and the autoregressive generative model restores the target pixel on the basis of a pixel value distribution for pixels adjacent to the target pixel in the source image.

Abstract: This disclosure relates to advanced image signal processing technology including encoded signals and digital watermarking. One implementation is directed to a printed object comprising: a white substrate or background comprising a first area; an ink mixture printed at a first plurality of spatial locations within the first area, the ink mixture printed such that the first area comprises a second plurality of spatial locations without the ink mixture, the ink mixture comprising extender white and Green 7 ink, the ink mixture comprising a volume or weight ratio of 97.5% to 99.75% white extender and 2.5%-0.25% Green 7 ink; in which the first plurality of spatial locations is arranged in a pattern conveying an encoded signal, and in which the white substrate or background and the ink mixture comprise a spectral reflectivity difference at or around 660 nm in a difference range of 8%-30%. Of course, other implementations, methods, packages, systems and apparatus are described in this patent document.

Abstract: A processing apparatus is described. The apparatus includes a plurality of processing cores, including a first processing core and a second processing core a first field programmable gate array (FPGA) coupled to the first processing core to accelerate execution of graphics workloads processed at the first processing core and a second FPGA coupled to the second processing core to accelerate execution of workloads processed at the second processing core.

Abstract: An image processing device according to an embodiment exemplarily includes, as an example: a processor that acquires a taken image obtained by imaging surroundings of a vehicle by an imaging unit mounted on the vehicle; projects the taken image to a stereoscopic projection plane including the vehicle and a first projection region rising above the vehicle and produces a composite image of the stereoscopic projection plane when viewed from a virtual viewpoint; causes a display to display the composite image; determines a target parking region in which the vehicle is parked in the stereoscopic projection plane; and shifts at least a part of a movement path of the vehicle from a position of the vehicle to the target parking region and the target parking region of the vehicle to a second projection region horizontal to the vehicle.

Abstract: An image style transform method includes: acquiring an initial image to be subjected to style transform; inputting a gradient of the initial image to an image style transform model, and obtaining a feature map of the initial image in a gradient domain from the image style transform model, where the image style transform model is obtained by being trained in the gradient domain based on a pixel-wise loss and a perceptual loss; and performing image reconstruction according to the feature map of the initial image in the gradient domain to obtain a style image.

Abstract: The present invention provides a method for providing with at least a portion of content having six degrees-of-freedom in a virtual environment, comprising: receiving, by at least one processor, the portion of content for the virtual environment; associating, by the at least one processor, at least one of a first geometric shape and a second geometric shape with the portion of content; projecting, by the at least one processor, the portion of content onto a first point of a surface of the first geometric shape; determining, by the at least one processor, based on the projecting of the portion of content onto the first point, a first outcome relating to the portion of content at the first position; projecting, by the at least one processor, the portion of content onto a second point of the surface of the first geometric shape or of a surface of the second geometric shape, the second point being different than the first point; determining, by the at least one processor, based on the projecting of the portion of

Abstract: Peripheral-vision expanded images are streamed to a video streaming client. The peripheral-vision expanded images are generated from source images in reference to view directions of the viewer at respective time points. View direction data is collected and received in real time while the viewer is viewing display images derived from the peripheral-vision expanded images. A second peripheral-vision expanded image is generated from a second source image in reference to a second view direction of the viewer at a second time point. The second peripheral-vision expanded image has a focal-vision image portion covering the second view direction of the viewer and a peripheral-vision image portion outside the focal-vision image portion. The second peripheral-vision expanded image is transmitted to the video streaming client.

Abstract: Systems and methods for unmanned aerial vehicle (UAV) course profiling are provided. A plurality of images may be captured by a UAV flying along a course at a first location. A profile may be constructed for the course based on the images captured by the UAV. The constructed course profile is transmitted over a communication network to a virtual reality system at a second location. The virtual reality system may generate a virtual environment corresponding to the course based on the constructed course profile, and a second UAV at the second location may fly along the virtual course.

Abstract: An image stitching processing method includes: obtaining a first image taken by a first camera module, wherein the first camera module has a first distance from a reference plane; obtaining a second image taken by a second camera module, wherein the second camera module has a second distance from the reference plane; scaling the second image according to a predetermined ratio and stitching the scaled second image with the first image to obtain a third image, wherein the third image has a stitching line between the first image and the scaled second image; determining whether an object image corresponding to an object in the third image is close to or located on the stitching line; identifying the object image to generate an identification confidence value; covering a standard object image on the object image to generate a modified third image; and outputting and displaying the modified third image.

Abstract: Provided is an information processing device configured to: acquire an image captured according to an imaging instruction by an imaging device mounted to a mobile object; acquire sensor information including position information about the mobile object from a sensor device according to a signal transmitted from the imaging device in response to the imaging instruction; and associate the acquired sensor information with the acquired image.

Abstract: The present disclosure provides a method, an electronic device, and a storage medium for obtaining a depth image. The method includes: mapping a depth image having a first resolution into a color image having a second resolution to obtain a processed image, the first resolution being smaller than the second resolution; establishing an objective function with respect to the processed image and a depth image having the second resolution, pixels in the processed image having one-to-one correspondence with pixels in the depth image having the second resolution, the objective function aiming to minimize an error with respect to the processed image and the depth image having the second resolution; and solving the objective function to obtain the depth image having the second resolution.

Abstract: The invention provides a reverse image display system. An image blocking module segments a reverse image into visual saliency image blocks and non-visual saliency image blocks according to visual saliency. A denoising module denoises the visual saliency image blocks by a BM3D algorithm, and denoises the non-visual saliency image blocks by a mean filtering algorithm. A composition module composites the denoised visual saliency image blocks and non-visual saliency image blocks into a final required reverse image which is transmitted to an automobile display screen for display. The visual saliency image blocks are denoised by the BM3D algorithm, so that the obtained image is more easily watched by human eyes, and the non-visual saliency image blocks are denoised by the mean filtering algorithm, denoising speed can be increased while certain image quality is maintained, and the denoising speed can be conveniently increased by a computer as a whole.

Abstract: In some examples, luminance-biased sharpening for thermal media printing may include converting an input image to a grayscale luminance representation. For each pixel of a plurality of specified pixels of the converted input image, a sharpening lightness value may be determined. Further, for each pixel of the plurality of specified pixels of the converted input image, a ratio of the sharpening lightness value to a corresponding original lightness value may be determined. Based on the determined ratio, a sharpened output image corresponding to the input image may be generated.

Abstract: The invention relates to an image processing apparatus for generating an HDR image associated with a first view on the basis of a plurality of LDR images, including a first LDR image and a second LDR image. The first LDR image is associated with the first view and a first exposure, i.e. a first dynamic range, and the second LDR image is associated with a second view and a second exposure, i.e. a second dynamic range. The image processing apparatus comprises a processor configured to provide a neural network having a plurality of neural subnetworks including a first neural subnetwork. The first neural subnetwork is configured to generate the HDR image on the basis of: (i) the first LDR image, (ii) the second LDR image, and (iii) a modified first LDR image. The modified first LDR image is associated with the first view and the second exposure.

Abstract: An image capture system comprises a camera configured to capture an image of a whiteboard, or similar, viewed from an acute angle. A linear polarizer has a surface substantially perpendicular to a plane of the board and an axis of polarization substantially perpendicular to the plane of the board or within 30° of the perpendicular to the plane of the board. The camera is configured to capture the image of the board through the polarizer. A normal to the polarizer is directed in a different direction to a direction defined by an optic axis of the camera.

Abstract: Provided are a system and method for correcting an image through estimation of a distortion parameter. The method includes receiving a distorted image including one or more measurement targets, extracting a plurality of feature points from each of the measurement targets, classifying the one or more measurement targets as a distorted target and an undistorted target by comparing distances between the plurality of extracted feature points and a center point of the received distorted image with each other, estimating a distortion parameter on the basis of standard deviations of a plurality of feature points of the classified distorted target and undistorted target, and correcting the received distorted image on the basis of the estimated distortion parameter.

Abstract: An apparatus is configured to convert a resolution of each of a plurality of images acquired by imaging an object under a plurality of geometric conditions based on an imaging position and a position of a light source that irradiates the object with light. The apparatus includes a determination unit configured to determine a resolution at which a number of peaks is one regarding a peak of a pixel value that emerges in a corresponding relationship between the pixel value and a geometric condition at each of pixel positions in the plurality of images, and a conversion unit configured to convert the resolution of each of the plurality of images into the determined resolution.

Abstract: A system comprising an apparatus for obtaining pixel intensity which is capable of assigning depth information to the pixel and is configurable to capture pixel intensity corresponding to multiple images; an image acquisition module operating on pixel intensity to access signal intensity data; a light segmentation module that analyzes the signal intensity data to detect intensity changes in each of the pixels to estimate pixel intensity present in regions associated with a subject of interest; a selective amplification module, configurable to apply tone correction and/or level shifting, that operates on each region to increase the intensity of the signal associated with the subject of interest relative to the intensity of other signals, producing a selectively-enhanced signal; and a HDR image composition module, taking the selectively-enhanced signal as an input and producing an image or image sequence based on the selectively-enhanced signal.

Abstract: A converter can process image data from input HDR images in real time to compute new metadata about the brightness, contrast, color gamut and/or color volume for the image data to be displayed from each frame. Existing metadata can be ignored. The converter can combine the metadata for a current HDR frame with metadata for a plurality of immediately previous sequential frames to provide parameters for tone mapping. The converter uses these parameters, and characteristics about a lower dynamic range display which will receive output image data, to define a transfer function for converting the input HDR image data into output image data for display. The converter analyzes and tone maps HDR frames at a rate sufficient to allow output video to be generated at a desired frame rate while receiving the image data from frames of the input HDR video at an input frame rate.

Abstract: Embodiments of the disclosure provide a video image processing method and apparatus thereof, and a display device, relate to the field of image processing technology, and in particular, and can solve the problem in the existing video image processing methods that real-time processing of a video image cannot be achieved due to large computational complexity. The video image includes multiple frames of image, and the method includes: obtaining a brightness characterization parameter representing image brightness for a current frame of image; obtaining a ratio of a brightness value of each input pixel in the current frame of image to the brightness characterization parameter; and obtaining a product of the ratio and a numerical value (M+1), wherein M is a maximum possible pixel brightness value of the current frame of image, and taking the product as a brightness value of an output pixel of the current frame of image. The invention can achieve contrast enhancement of a video image.

Abstract: A method, processor and system of retaining dynamic range. The method comprises obtaining a vignetting correction mesh for image data. The method also comprises generating an intensity compression curve, the intensity compression curve comprising one or more segments, based on the vignetting correction mesh; and adjusting pixel values of a portion of the image data according to the intensity compression curve and vignetting correction mesh.

Abstract: An image processing method, an image processing system and a storage medium are provided. The image processing method includes: acquiring an initial image; extracting a contour of a predetermined target included in the initial image during a transmission process of pixel data of the initial image; and obtaining information of the predetermined target according to the contour of the predetermined target included in the initial image.

Abstract: In some embodiments, an image manipulation application receives, via a user interface, an input to manipulate an image displayed at a target resolution. The image manipulation application determines a normalized number of tracker events between two consecutive renditions of the image caused by manipulating the image based on the input. Based on the normalized number of tracker events, the image manipulation application selects a version of the image from a set of versions of the image that have different resolutions of the image including the target resolution. The selected version of the image has a lower resolution than the target resolution. The image manipulation application manipulates the selected version of the image based on the input and generates an updated image for display in the user interface in the next rendition of the image.

Abstract: The present disclosure relates to a method, an apparatus and a device for converting a style of an image, wherein the method comprises: acquiring a luminance component (Y) and chrominance components (U, V) in a YUV space of an image to be processed; performing a group convolution processing on the luminance component (Y) and the chrominance components (U, V) in the YUV space of the image to be processed to obtain content features and style features of the image to be processed; and performing a fusion processing on the content features, the style features and target style features of the image to be processed to convert the image to be processed into an image of a target style.

Abstract: The disclosure provides an image blending method. The method includes projecting a first image and a second image onto a projection surface by a first projector and a second projector, respectively, and the first image and the second image overlap each other; and projecting the first control pattern onto the first image, adjusting the first control pattern such that a first control pattern frame matches a boundary of an overlapping area, and thereby identifying a position of a first non-overlapping area in the first image. Additionally, a similar operation is performed by the second projector to identify a second non-overlapping area in the second image. All pixels in the first non-overlapping area and the second non-overlapping area are adjusted such that the black-level brightness of the first non-overlapping area and the second non-overlapping area correspond to the black-level brightness of the overlapping area to obtain better brightness uniformity.

Abstract: An image processing method includes reading first image data from a memory, storing the first image data in a line buffer, processing the first image data to generate a first partial image, writing the first partial image into the memory, reading second image data from the memory, storing the second image data in the line buffer, processing the second image data to generate a second partial image, reading the first partial image from the memory, and splicing the first and the second partial images to obtain an output image. The first image data and the second image data correspond to a same original image having L rows and K columns of pixels. The first image data includes L rows and M columns of pixel data, and the second image data includes L rows and N columns of pixel data. K is larger than or equal to M plus N.

Abstract: A computer-implemented method is provided for image-based defect detection. The method includes performing, by a processor device, template matching and subtraction on a set of training images and at least one template image to obtain a set of difference images. The difference images have defects, if any, highlighted therein. The method further includes generating, by the hardware processor applying a binary classification model to each of the training images in the set, activation heatmaps. The method also includes identifying, by the hardware processor, rough defect areas of interest in the activation heatmaps. The method additionally includes super-imposing, by the hardware processor, the activation heatmaps onto the difference images to obtain a set of super-imposed images, and highlight, as true defect areas, any areas in the super-imposed images having the defects from the difference images that overlap with the rough defect areas of interest from the activation heatmaps.

Abstract: A memory stores shape information representing a shape of an object. A processor detects a plurality of feature lines from an image of an object that has been captured by an image capturing device in a manufacturing process of manufacturing the object, and produces a plurality of combinations by correlating each of a plurality of line segments in the shape information and each of the plurality of feature lines with each other. Next, the processor performs classification of each of the combinations into an identified combination that has a certain correlation result or an unidentified combination that has an uncertain correlation result. The processor also changes a result of the classification for the identified combination and the unidentified combination according to a reliability of each of the plurality of combinations and determines a degree of progress of the manufacturing process by using the identified combination included in the changed result.

Abstract: A device for inspecting a display device includes a camera to photograph a substrate and generate image information, a pixel value setter to set pixel values corresponding to respective luminances of a plurality of pixels from the image information, and to detect a crack region based on the pixel values, a stress calculator to calculate a critical stress of a crack included in the crack region, and a determiner to check whether the critical stress is equal to or greater than a first threshold value and to determine whether the substrate has defects. The stress calculator calculates a critical stress of the substrate by using fracture toughness, a shape factor, and a crack depth. The shape factor is set to increase as a compressive stress of the substrate increases.

Abstract: A method is described for ways to generate a Fraction of Sand (Fsand) estimate and net-to-gross (NTG) estimate of sand in a formation using a machine-learning algorithm such as a neural network based on borehole image logs. The method may use the Fsand and other information to estimate hydrocarbons in place in a subsurface formation. The method may be executed by a computer system.

Abstract: Systems and methods for detecting anomaly in video data are provided. The system includes a generator that receives past video frames and extracts spatio-temporal features of the past video frames and generates frames. The generator includes fully convolutional transformer based generative adversarial networks (FCT-GANs). The system includes an image discriminator that discriminates generated frames and real frames. The system also includes a video discriminator that discriminates generated video and real video. The generator trains a fully convolutional transformer network (FCTN) model and determines an anomaly score of at least one test video based on a prediction residual map from the FCTN model.

Abstract: The present application relates to a characterization method for fine-grained sedimentary rock laminar texture, including S1: image preprocessing; S2: loading the image, and normalizing the image to a specified size; S3: performing mean filtering, dilation operation and binarization processing on the image; S4: determining whether laminars are developed; S5: determining the number of bright laminars and dark laminars; S6: determining the continuity of bright laminars and dark laminars; S7: according to the statistical result and the calculation result, recording the characterized parameters into Excel. The present application can accurately characterize the texture features of fine-grained sedimentary rock laminar. Compared with the prior art, the present application have higher efficiency and satisfies the requirement of symmetrically depicting the growth features of fine-grained sedimentary rock laminar, and a technical support is provided for the exploration and development of shale oil and gas.

Abstract: A method performed by one or more devices is disclosed. The method includes detecting a first image information item indicative of at least one soiling on a textile, determining a soiling information item indicative of at least one property of the soiling on the textile where the at least one property is determined based at least in part on the detected first image information item and the at least one property of the soiling is determined based at least in part on a property dependent on the outline of the soiling, and outputting or causing the outputting of the determined soiling information item. Furthermore, a device and a system for performing the subject method is disclosed.

Abstract: In a singular part detection system (1), a singular part (13) having an arbitrary feature is extracted from a captured image (12) of a subject captured by an imaging unit (2) by a singular part extracting unit (3), a singular part image (17) with an arbitrary size is cut out from the captured image (12) by a singular part image cutting unit (4) such that the singular part (13) overlaps the center (C) of the singular part image (17), and a type of the singular part (13) is identified by an identification unit (5) using machine learning with the singular part image (17) as an input.

Abstract: In a singular part detection system, a singular part having an arbitrary feature is detected from a captured image of a subject captured by an imaging unit by a singular part detecting unit, a singular part image with an arbitrary size is cut out from the captured image by a singular part image cutting unit such that the singular part overlaps the center of the singular part image, and a type of the singular part is identified by an identification unit using machine learning with the singular part image as an input.

Abstract: A device includes image generation circuitry and a convolutional neural network. The image generation circuitry, in operation, generates a binned representation of a wafer defect map (WDM). The convolutional-neural-network, in operation, generates and outputs an indication of a root cause of a defect associated with the WDM based on the binned representation of the WDM and a data-driven model associating WDMs with classes of a defined set of classes of wafer defects.

Abstract: The present disclosure provides a method and a system for scanning wafer. The system captures a defect image of a wafer, and generates a reference image corresponding to the first defect image based on a reference image generation model. The system generates a defect marked image based on the defect image and the reference image.

Abstract: A computing device is used to capture image data of a physical environment. The image data is analyzed to determine color information for colors represented in the physical environment and to determine scene information that describes a room type associated with the physical environment. A palette of colors is assembled using the colors from the color information and provided for display. Upon selection of a color from the palette of colors, a product associated with the selected color and with the room type is provided for display.

Abstract: A device for detecting a group of offending objects and determining that the number of offending objects is above a predetermined threshold of offending objects. The device uses an image capturing system to scan areas to detect flying objects such as flying insects to detect a presence of a swarm of such flying objects. An action head on the device is configured to automatically respond once a swarm of objects is identified. The action head may disperse the swarm by expelling a substance such as a mist, smoke, repellant or insecticide.

Abstract: A system for detecting motion in one or more images of a video feed captured by an image capture device. The system collects the multiple images of the video feed and segments each image into multiple portions or cells. Multiple cell groups are determined based on the images, with each cell group including information relating to contents of set of a common portion of the multiple images. A difference metric is calculated for each of the cell groups and at least one level of change of values of the difference metric is determined. The at least one level of change is data representing the video feed that is compared with a still-scene data model associated with the image capture device to determine a respective probability that each of the cell groups includes motion. Motion is identified for those cell groups that have a probability greater than or equal to a threshold value. The system generates a transformed video feed including the video feed and a visual indication of the motion.

Abstract: We present a method to detect dots in microscope images of tissue samples for the purpose of diagnosis or therapy selection. Dots in tissue arise trough CISH or FISH staining, but also through staining of small cellular compartments, or in other ways. The method is applicable to both brightfield and fluorescence modalities, as well as mass spectrometry imaging methodologies. The method is based on the use of first and second derivatives of the image along the image axes, computed using regularized derivative operators, i.e. Gaussian derivatives. The outputs of these operators are examined at appropriate distances from each location in the image. The found values must have specific signs. If the signs are all correct, these values are multiplied together to obtain a confidence measure for a dot being present at that location. If the signs do not match, no dot is present, and a zero is output.

Abstract: An automated parsing pipeline system and method for anatomical localization and condition classification is disclosed. The system comprises an input even source, a memory unit and processor including a volumetric image processor, a voxel parsing engine, localization layer and a detection module. The volumetric image processor is configured to receive volumetric image from the input source and parse the received volumetric image. The voxel parsing engine is configured to assign each voxel a distant anatomical structure. The localization layer is configured to crop a defined anatomical structure with surroundings. The detection module is configured to classify conditions for each defined anatomical structure within the cropped image. The disclosed system and method provide accurate localization of a tooth and detects several common conditions in each tooth.

Abstract: A method for removing ghost markers from a measured set of medical markers, wherein the measured set of markers represents the positions of real markers and the positions of ghost markers, comprising the steps of: —calculating all possible minimal marker sets, wherein a minimal marker set is a subset of the measured set and a minimal marker set consists of the smallest possible number of markers which would cause the measured set to be measured; —calculating the smallest extent of each minimal marker set, wherein the smallest extent is the smallest extent among the extents in three orthogonal directions; and —selecting the minimal marker set having the smallest out of the smallest extents as a marker set without ghost markers.

Abstract: The method according to the invention utilizes a color decomposition of histological tissue image data to derive adensity map.The density map corresponds to the portion of the image data that contains the stain/tissue combination corresponding to the stroma, and at least one gland is extracted from said density map. The glands are obtained by a combination of a mask and a seed for each gland derived by adaptive morphological operations, and the seed is grown to the boundaries of the mask.The method may also derive an epithelial density map used to remove small objects not corresponding to epithelial tissue. The epithelial density map may further be utilized to improve the identification of glandular regions in the stromal density map.The segmented gland is extracted from the tissue data utilizing thegrown seed as a mask. The gland is then classified according to its associated features.