Abstract: The present invention relates to a method of detecting an edge (or a contour line) of a pattern, which is formed on a workpiece (e.g., a wafer or a mask) for use in manufacturing of semiconductor, from an image generated by a scanning electron microscope. The pattern-edge detection method includes: generating an objective image of a target pattern formed on a workpiece; generating a feature vector representing features of each pixel constituting the objective image; inputting the feature vector to a model constructed by machine learning; outputting, from the model, a determination result indicating whether the pixel having the feature vector is an edge pixel or a non-edge pixel; and connecting a plurality of pixels, each having a feature vector that has obtained a determination result indicating an edge pixel, with a line to generate a virtual edge.

Abstract: A method to design miniature wide-angle and ultra-wide-angle lenses by using on-purpose distortion to have shorter focal length than usual for a given image sensor size and a desired image projection. This results in optical systems having miniaturization ratio, defined as the ratio between the total track length and the image footprint diameter, smaller than 0.8. The resulting image from these systems having on-purpose distortion can then be processed with a processor to remove the on-purpose distortion and to output an image with the targeted distortion profile.

Abstract: Hierarchical systems and methods for automatic container type recognition from images are disclosed herein. An example embodiment includes a system for image analysis, comprising: a container recognition component; a character recognition component; and a 3D point cloud component; wherein the container recognition component is configured to receive an image and produce one of three outputs based on analysis of the image such that the output corresponds to either a container is identified, further analysis is performed by the character recognition component, or further analysis is performed by the 3D point cloud component.

Abstract: A mirror assembly (100) comprising: a reflective portion (110) configured to reflect incident light; a display unit (120) arranged to overlap the reflective portion, wherein the display unit is configured to display at least one of a visual element and a blurred effect element; and a control unit (130). The control unit (130) is configured to: receive instruction to display a visual element or instruction to display a blurred effect element; determine, based on the received instruction, a blur region for the visual element or a motion trajectory of the blurred effect element, wherein the blur region or the blurred effect element is larger than a display resolution of the display unit; and control the display unit to display the visual element with the determined blur region or to display the blurred effect element in the determined motion trajectory in a field of view of a user.

Abstract: A method for processing an image and a mobile terminal. The method includes: obtaining a lens effect instruction, and determining a target blurring algorithm from a plurality of preset blurring algorithms based on the lens effect instruction, in which the blurring algorithms are algorithms for simulating optical lens effects; and obtaining a target image by blurring an image to be processed based on the target blurring algorithm.

Abstract: The objective of the present invention is provide a defect inspection apparatus that increases defect position precision and can easily align a coordinate origin offset between a reviewing apparatus and the defect inspection apparatus, even when design data cannot be obtained or it is difficult to sufficiently use the design data. The defect inspection apparatus according to the present invention acquires a wafer swath image necessary for inspection, and uses the swath image to detect defects and calculate a positional deviation amount. During the calculation of the positional deviation amount, a template pattern is acquired from one arbitrary swath image via an image processing unit, and the template pattern and a plurality of swath images of the entire wafer are compared, whereby the positional deviation amount for a position corresponding to the template pattern on the wafer is calculated.

Abstract: An apparatus comprises an interface and a processor. The interface may be configured to receive pixel data.

Abstract: A projection system and calibration method therefore relate to a light source configured to emit a light in response to an image data, an optical system configured to project the light emitted by the light source; receiving an input associated with a plurality of light values corresponding to a plurality of primary lightfields; converting the input associated with the plurality of light values to a plurality of projector primary color values; determining a gain map based on the plurality Values of projector primary color values; applying the gain map to an image to perform a chromaticity uniformity correction by adjusting levels of the plurality of primary lightfields so that a primary mixture is the same over an image frame, and projecting the image with the optical system in the image frame, wherein the second image is corrected by the gain map.

Abstract: A method of fusing images includes obtaining an optical image of a first scene with a first camera. A thermal image of the first scene is obtained with a second camera. The optical image is fused with the thermal image to generate a fused image.

Abstract: An information processing apparatus includes a computer executing instructions that, when executed by the computer, cause the computer to acquire an image captured by an image capturing apparatus, to cause a display to display the acquired image, and to perform control process for controlling an image capturing range of the image capturing apparatus. A first placement candidate in which an object in the image capturing range is placed at a first position, and a second placement candidate in which the object in the image capturing range is placed at a second position different from the first position are displayed on the display. In a case where one of the first and the second placement candidates is selected by a user, the image capturing range is controlled based on information of the selected placement candidate.

Abstract: A camera microcomputer of an imaging device determines a feature region of an object according to information on a moving direction of the object with respect to the imaging device. Then, the camera microcomputer determines a reference region for correcting image blur related to the object on the basis of a motion vector of the object related to the feature region obtained on the basis of a motion between a plurality of images.

Abstract: Systems, apparatuses, and methods for performing optimized sharpening of images in non-linear and linear formats are disclosed. A system includes a blur filter and a sharpener. The blur filter receives an input image or video frame and provides blurred output pixels to a sharpener unit. The sharpener unit operates in linear or non-linear space depending on the format of the input frame. The sharpener unit includes one or more optimizations to generate sharpened pixel data in an area-efficient manner. The sharpened pixel data is then driven to a display.

Abstract: A method for reducing jitter of an optical sensor when in a stationary condition includes: receiving a plurality of raw delta; comparing a movement of the optical sensor with a predetermined threshold; and when the movement is less than the predetermined threshold, entering a dynamic downshift mode, including: storing raw delta into a buffer; when the buffer is not full, outputting the raw delta as reported delta; and when the buffer is full, calculating an average of the total raw delta stored in the buffer, and outputting the average delta as reported delta.

Abstract: An object is to cause a distribution of defocus amounts in a certain arbitrary region of a captured image to be displayed. A map data generation unit configured to generate defocus map data representing defocus amounts at a plurality of positions in a captured image obtained by an imaging element unit, calculated from phase difference information detected by a phase difference detection unit, and a display control unit configured to generate a defocus map image representing a distribution of defocus amounts of the captured image using the defocus map data generated by the map data generation unit and to perform display control are included.

Abstract: A method includes training a first model to measure the banding artefacts, training a second model to deband the image, and generating a debanded image for the image using the second model. Training the first model can include selecting a first set of first training images, generating a banding edge map for a first training image, where the map includes weights that emphasize banding edges and de-emphasize true edges in the first training image, and using the map and a luminance plane of the first training image as input to the first model. Training the second model can include selecting a second set of second training images, generating a debanded training image for a second training image, generating a banding score for the debanded training image using the first model, and using the banding score in a loss function used in training the second model.

Abstract: Methods to solve the problem of performing fusion of images acquired with two cameras with different type sensors, for example a visible (VIS) digital camera and an short wave infrared (SWIR) camera, include performing image space equalization on images acquired with the different type sensors before performing rectification and registration of such images in a fusion process.

Abstract: A scalable hardware accelerator configured to compute video quality metrics is disclosed. In some embodiments, an accelerator for video quality metrics comprises an application-specific integrated circuit that includes a buffer memory configured to store at least a portion of a reference frame of a video and at least a corresponding portion of a distorted frame of a transcoded version of the video and that includes a processing unit configured to receive data from the buffer memory and compute a perception-based video quality metric for the distorted frame with respect to the reference frame.

Abstract: Sharpness at each focus position is calculated as an individual sharpness. Thereafter, one or M (where M is a natural number equal to or greater than 2 and smaller than N) corrective sharpness are calculated and image reference values are determined from the individual sharpness. An luminance value is calculated based on the image reference values and the corrective sharpness for each pixel. An all-in-focus image is generated by combining those luminance values.

Abstract: A method for detecting a finger is provided. The method includes obtaining a plurality of digital images including a first digital image captured by a camera from a field of view containing a background and a hand including at least one finger, and obtaining an identification of pixels of the plurality of digital images that correspond to at least one finger that is visible in the plurality of digital images rather than to the background, the pixels being identified by: obtaining, from the digital images, a Gaussian brightness falloff pattern indicative of at least one finger, identifying an axis of the at least one finger based on the obtained Gaussian brightness falloff pattern indicative of the at least one finger without identifying edges of the at least one finger, and identifying the pixels that correspond to the at least one finger based on the identified axis.

Abstract: A method and apparatus for image processing are provided. A mask is obtained by separating an original image into a background image and a foreground image. A partial stylized image is obtained by transforming the background image or the foreground image according to a selected style. A stylized image is obtained according to the mask and the partial stylized image.

Abstract: Provided are a cell image evaluation device, method, and program which are capable of more accurate and high reliable evaluation even though a captured image of each part to be observed within a container deteriorates. The cell image evaluation device includes an image evaluation unit that evaluates a state of a cell included in a captured image obtained by capturing an inside of the container that contains the cell based on the captured image, and a deterioration determination unit that determines whether or not the captured image deteriorates. The image evaluation unit changes an evaluation method of the captured image according to a determination result of the deterioration determination unit.

Abstract: A method of digitally processing an image comprises: generating an intensity distribution model (170) in respect of at least a portion of the array of sensing pixels (102) of a detector device (100). The array of sensing pixels comprises clusters of pixels. A pixel (140) from the array of sensing pixels is then selected (202) and a first distance and a second distance from the selected pixel to a first neighbouring pixel (142) and a second neighbouring pixel (144), respectively, are determined (402) and the intensity distribution model (170) referenced (406) by the first distance is used to calculate a first weight and a second weight to apply to the first and second neighbouring pixels, respectively. The first distance comprises an intra-cluster distance and the second distance comprises an inter-cluster distance, the intra-cluster distance being different from the inter-cluster distance.

Abstract: A method for reducing jitter of a mouse when in a stationary condition, including: receiving a plurality of raw delta; comparing a movement of the mouse with a predetermined threshold; and when the movement is less than the predetermined threshold, entering a dynamic downshift mode. Entering the dynamic downshift mode includes: storing raw delta into a multi-tap buffer; when the multi-tap buffer is not full, outputting the raw delta as reported delta; and when the multi-tap buffer is full, calculating an average of the total raw delta stored in the multi-tap buffer, and outputting the average delta as reported delta.

Abstract: A method includes capturing, by a camera disposed behind a display panel of an electronic device, an original image through a semi-transparent pixel region of the display panel, and determining a depth position with respect to at least one object identified within the original image. The method further includes accessing, based on the depth position, a plurality of point spread functions (PSFs) corresponding to a plurality of lateral positions at the depth position, and generating a set of image patches based on the plurality of PSFs. Each image patch of the set of image patches is generated based on a different one of the plurality of PSFs. The method concludes with generating a reconstructed image corresponding to the original image based on the set of image patches.

Abstract: A method for mitigating motion blur in a visual-inertial tracking system is described. In one aspect, the method includes accessing a first image generated by an optical sensor of the visual tracking system, accessing a second image generated by the optical sensor of the visual tracking system, the second image following the first image, determining a first motion blur level of the first image, determining a second motion blur level of the second image, identifying a scale change between the first image and the second image, determining a first optimal scale level for the first image based on the first motion blur level and the scale change, and determining a second optimal scale level for the second image based on the second motion blur level and the scale change.

Abstract: An image processor eliminates a character or object from a sequence of frames and then merges the resulting images with those of nearby frames, both preceding and succeeding, to synthesize the background of the sequence of frames.

Abstract: A method of operating an electronic device includes displaying a preview image in response to execution of a camera application, extracting feature information from the preview image, converting user input to an input value in response to the user input generated on the preview image, setting a depth based on the feature information and the input value, and generating a result image in accordance with the depth in response to execution of an imaging operation.

Abstract: Systems and methods are directed to inpainting video. More specifically, initial video data including a sequence of image frames containing missing or corrupted pixel information may be received. Optical flow displacement values and optical flow validity masks may be generated for neighboring image frames of initial video data. Image features from image feature maps of one or more neighboring image frames may be warp-shifted to image feature maps of a current image frame using the optical flow displacement values and warp-shifted image features from the feature maps of the one or more neighboring image frames may be selected based on one or more of the optical flow validity masks. A sequence of complete image frames may be generated based on the selected warp-shifted image features from the feature maps of the one or more neighboring image frames and image features from the image feature maps of the current image frame.

Abstract: A method of encoding a video data signal (15) is provided, together with a method for decoding. The encoding comprises providing color information (51) for pixels in an image, providing a depth map with depth information (52) for the pixels, providing transition information (56, 57, 60, 70, 71) being representative of a width (63, 73) of a transition region (61, 72) in the image, the transition region (61, 72) comprising a depth transition (62) and blended pixels in which colors of a foreground object and a background object are blended, and generating (24) the video data signal (15) comprising encoded data representing the color information (51), the depth map (52) and the transition information (56, 57, 60, 70, 71). The decoding comprises using the transition information (56, 57, 60, 70, 71) for determining the width (63, 73) of the transition regions (61, 72) and for determining alpha values (53) for pixels inside the transition regions (61, 72).

Abstract: A method for deblurring a blurred image includes encoding, by at least one processor, a blurred image at a plurality of stages of encoding to obtain an encoded image at each of the plurality of stages; decoding, by the at least one processor, an encoded image obtained from a final stage of the plurality of stages of encoding by using an encoding feedback from each of the plurality of stages and a machine learning (ML) feedback from at least one ML model; and generating, by the at least one processor, a deblurred image in which at least one portion of the blurred image is deblurred based on a result of the decoding.

Abstract: An image processing device according to the present invention includes: a memory; and at least one processor coupled to the memory. The processor performs operations. The operations includes: detecting a feature point to be used for authentication of a target object included in an image; calculating a first blur being a blur of a predetermined processing point in the feature point; and estimating, by using the first blur, a second blur being a blur of the target object.

Abstract: A system and method for improving a video characteristic of a video stream is described. According to various implementations of the invention, a changed region between a later-in-time image frame and an earlier-in-time image frame and an unchanged region between such two image frames are determined. A new improvement to the video characteristic is determined and applied to the changed region of the later-in-time image frame. A prior improvement to the video characteristic that was determined for the earlier-in-time image frame is applied to the unchanged region of the later-in-time image frame.

Abstract: Systems and methods for implementing array cameras configured to perform super-resolution processing to generate higher resolution super-resolved images using a plurality of captured images and lens stack arrays that can be utilized in array cameras are disclosed. An imaging device in accordance with one embodiment of the invention includes at least one imager array, and each imager in the array comprises a plurality of light sensing elements and a lens stack including at least one lens surface, where the lens stack is configured to form an image on the light sensing elements, control circuitry configured to capture images formed on the light sensing elements of each of the imagers, and a super-resolution processing module configured to generate at least one higher resolution super-resolved image using a plurality of the captured images.

Abstract: Systems and methods are provided for receiving, at a server, a selection of an anchor product from an electronic catalog stored in at least one storage device communicatively coupled to the server, and vectorizing at least one of text and images associated with the selected anchor product and other products in the catalog. At least one of key words may be determined from text data and key images from image data for each product of the catalog. Vectors may be formed from at least one of the keywords and key images, and concatenating the separate vectors together to form final vectors for the products. A similarity search may be performed using the final vectors to determine a group of similar products from the vectorized products of the catalog. Selected products that are within a same slot as the anchor product may be labelled in batch.

Abstract: An image processing method and device, storage medium and electronic device for deblurring an image. The method includes obtaining an image processing instruction including an instruction to deblur a target blurred image; obtaining a target model by training an original model based on a plurality of sample images of different scales, one of the plurality of sample images being a blurred image composed of a plurality of clear images, and the obtained target model being used for deblurring the blurred image to obtain a clear image; based on the image processing instruction, using the target model to deblur the target blurred image to obtain a target clear image; and outputting the target clear image.

Abstract: Embodiments of this application provide an image processing method performed at a computing device. The image processing method includes: obtaining a to-be-processed image with ghost reflection; calculating an image gradient of the to-be-processed image; determining, according to the image gradient, a gradient of a target image obtained after the ghost reflection is removed from the to-be-processed image; and generating the target image based on the gradient of the target image. According to the technical solution of the embodiments of this application, the ghost reflection in the image can be effectively removed, ensuring high quality of a processed image.

Abstract: The present disclosure provides method and system for auto focusing a microscopic imaging system using machine learned regression system such as Convolutional Neural Network (CNN). The method comprises receiving a first image of a sample under review and a second image of sample wherein the first image is captured at first focus position and second image is captured at second focus position. The CNN is trained using the plurality of historic difference images along with direction of focus and optimal focus position. The difference of two images are obtained in terms of difference in pixel values. The direction of focus and optimal focus position for difference image is identified based on plurality of historic difference images along with direction of focus and optimal focus position. The method enables automated stage comprising sample to move towards direction of focus and position at optimal focus position for capturing a focused image.

Abstract: An image processing device acquires a captured image and a depth image. A region dividing section divides the plane of the captured image into regions by determining distance values indicated by the depth image with respect to a preset threshold value (region-divided image). A compressing section generates and outputs data of a captured image having different levels of detail in the respective regions, with respect to the resolution and the number of gradations representing pixel values of the captured image, according to the result of the region division.

Abstract: A vehicle includes one or more cameras that capture a plurality of two-dimensional images of a three-dimensional object. A light detector and/or a semantic classifier search within those images for lights of the three-dimensional object. A vehicle signal detection module fuses information from the light detector and/or the semantic classifier to produce a semantic meaning for the lights. The vehicle can be controlled based on the semantic meaning. Further, the vehicle can include a depth sensor and an object projector. The object projector can determine regions of interest within the two-dimensional images, based on the depth sensor. The light detector and/or the semantic classifier can use these regions of interest to efficiently perform the search for the lights.

Abstract: Systems and methods to provide visual references to passengers in vehicles to prevent motion sickness. The system can include a controller and one or more projectors and/or displays. The controller can detect movement of a vehicle and project images within the vehicle that comport with the detected movement. The system can include a projector to project images on the interior of the vehicle. The system can include one or more displays to display images inside the vehicle. The controller can receive data from one or more cameras, accelerometers, navigation units, magnetometers, and other components to detect the motion of the vehicle. The system can display visual references on the dashboard, door panels, and other interior surfaces to complete the view of passengers, or provide other visual reference, to prevent motion sickness.

Abstract: A system and method for refocusing an image including determining a point spread function (PSF) according to region of interest (ROI) and pixel depth, and converting the PSF to a gradient domain including differentiating the PSF to reduce nonzero elements in the PSF. The technique spreads intensity of pixels into a circle of confusion per the differentiated PSF. A shape of an optical system or aperture of the imaging device may be considered.

Abstract: An imaging device (1a, 1b, 1c, 1d, 1e, 1f) includes at least one imager (Cam0, Cam1, Cam2, Cam3, Cam4, Cam5, Cam6, Cam7) including an imaging element (210, 212) configured to receive light incident through a lens (240); and a casing (10a, 10b, 10c 10d 10e, 10f) at which at least four of the imagers are arranged, the casing being configured such that each one of the imagers and another one of the imagers have optical axes substantially parallel to each other and have opposite incident directions of light on the optical axes, and each one of the imagers is arranged outside imagable ranges of the other imagers.

Abstract: There is provided an apparatus with a sample holder to hold a sample to be imaged. An image capture device has a field of view and captures an image of the field of view. Also provided is an actuator. A controller controls the actuator to cause relative movement between the sample holder and the image capture device at a given speed and at a given direction during an exposure time of the image capture device such that, in use, the sample moves across at least a portion of the field of view during the exposure time. A processor performs a deblur algorithm to deblur the image using the given speed and the given direction.

Abstract: A method and system for determining an optimal wireless channel for a Wi-Fi access point in a cloud-based software defined network (SDN) using an Application Programming Interface (API) is described. Initially, the API collects the measurement information and media access control (MAC) addresses from a plurality of nearby Wi-Fi access points to a client device. The measurement information is analyzed to determine a location of the client device using an Artificial Intelligence (AI) model. To determine the location of the client device, the API creates a plurality of clusters of Wi-Fi access points and updates the plurality of clusters with one or more newly identified Wi-Fi access points. Thereafter, the API calculates an optimal wireless channel for a Wi-Fi access point from the cluster using the AI model and enables the client device to automatically switch to the optimal wireless channel for connecting with the Wi-Fi access point.

Abstract: A sample positioning system is disclosed. The system may include an imaging detector. The system may further include a controller communicatively coupled to the imaging detector and a sample stage, the controller including one or more processors configured to execute program instructions causing the one or more processors to: receive a current position of a field of view of the imaging detector; receive a target position of the sample; receive locations of reference features along a path; direct the sample stage to translate the sample along the path; direct the imaging detector to capture images of the reference features along the path; determine positioning errors of the sample stage along the path based on the images of the reference features; and adjust at least one of a velocity of the sample stage or the path to the target location based on the positioning errors during translation.

Abstract: An object of the present invention is to generate a high-dynamic-range image with fewer pseudo-contours. An apparatus of the present invention generates a high-dynamic-range image and includes a setting unit for setting an imaging condition for each region that constitutes an image. The apparatus includes a setting unit configured to set an exposure condition for the region and a correcting unit configured to correct the set exposure condition so that a difference between a maximum value and a minimum value out of the set exposure condition is small.

Abstract: Devices, methods, and non-transitory program storage devices are disclosed herein to provide improved image processing, the techniques comprising: obtaining an input image and target image data, and then calculating derivatives for the target image data using a regularized derivative kernel operator. In some embodiments, the regularized operator may comprise the following operator: [?1 (1+?)], wherein ? may be a controllable system parameter and preferably is independent of the particular type of image processing being applied to the image. In some embodiments, the techniques may find look-up table (LUT) mappings or analytical functions to approximate the derivative structure of the target image data. Finally, the techniques disclosed herein may generate an output image from the input image based on attempting to closely approximate the calculated derivatives for the target image data. In preferred embodiments, by controlling the mapping, e.g.

Abstract: A method for correcting blur effects is presented. The method includes generating a plurality of images from a camera, synthesizing blurred images from sharp image counterparts to generate training data to train a structure-and-motion-aware convolutional neural network (CNN), and predicting a camera motion and a depth map from a single blurred image by employing the structure-and-motion-aware CNN to remove blurring from the single blurred image.

Abstract: An apparatus executes the instructions to create a combined image by performing combining processing using a plurality of images of an object captured at different focus positions in an optical axis direction, and acquire contrast values of the plurality of images. A depth of field of the combined image is deeper than a depth of field of each of the plurality of images. The at least one processor further executes instructions to calculate a combining ratio used in the combining processing using the contrast values of the plurality of images. An image in which the object is not in focus among the plurality of images is determined using the contrast values of the plurality of images, and the determined image is not used in the combining processing.

Abstract: An imaging device is provided that can correct more accurately an image shake. The imaging device includes an imaging element taking an object image to generate image data, a gyro sensor unit including a gyro sensor, an image-shake correction unit holding the imaging element, moving the imaging element based on an output of the gyro sensor, and correcting a shake of an object image taken by the imaging element, and a mount base holding the gyro sensor unit and the image-shake correction unit.