Abstract: A normal candidate information generation unit of an information processor generates normal candidate information for each pixel indicating, for example, a zenith angle, or an azimuth angle, or a zenith angle and an azimuth angle, on the basis of a polarization image in a plurality of polarization directions obtained by a polarization imaging unit. The in-plane pixel selection unit selects a plurality of pixels indicating the plane to be observed in the polarization image. A normal calculation unit calculates a normal of the plane to be observed on the basis of the normal candidate information of the pixels selected by the in-plane pixel selection unit.

Abstract: A method and an image processing device for mura detection on a display are proposed. The method includes the following steps. An original image of the display is received and segmented into region of interest (ROI) patches. A predetermined range of spatial frequency components are filtered out from the ROI patches to generate filtered ROI patches. A mura defect is identified from the display according to the filtered ROI patches and predetermined mura patterns.

Abstract: A device and a method for detecting cigarette fly ash by a gray-scale difference based on machine vision (MV) are provided. A manipulator holds a cigarette as a detection sample to simulate a human smoking action, and multiple groups of cameras track a simulated smoking process of the detection sample synchronously in real time. It is determined whether fly ash appears based on a gray-scale difference of burning ash columns, produced without being subjected to flicking, in acquired images. A fly ash area of the burning ash columns of the cigarette is calculated by an area with the gray-scale difference of the burning ash columns of the cigarette in two sequential images of the burning ash columns of the cigarette, and a fly ash amount is further determined. The detection of the amount of fine fly ash is converted into the detection of the gray-scale difference.

Abstract: A method for calibrating the position and orientation of a camera, in particular a vehicle-mounted camera, relative to a calibration pattern includes the steps of: A] acquiring an image of the calibration pattern by the camera; B] determining a parameter of the image or of the calibration pattern; C] transforming the image based on the parameter; D] identifying characteristic points or possible characteristic points of the calibration pattern within the transformed image; E] deriving the position or orientation of the camera relative to the calibration pattern from the identified characteristic points or possible characteristic points; F] in dependence of a confidence value of the derived position or orientation of the camera or in dependence of the number of iterations of steps B to F so far, repeating steps B to F; and G] outputting the position or orientation of the camera derived in the last iteration of step E.

Abstract: Introduced here are techniques for relighting an image by automatically segmenting a human object in an image. The segmented image is input to an encoder that transforms it into a feature space. The feature space is concatenated with coefficients of a target illumination for the image and input to an albedo decoder and a light transport detector to predict an albedo map and a light transport matrix, respectively. In addition, the output of the encoder is concatenated with outputs of residual parts of each decoder and fed to a light coefficients block, which predicts coefficients of the illumination for the image. The light transport matrix and predicted illumination coefficients are multiplied to obtain a shading map that can sharpen details of the image. Scaling the resulting image by the albedo map to produce the relight image. The relight image can be refined to denoise the relight image.

Abstract: A method and a system for image correction are provided. The system includes an image processor that performs the method for image correction when receiving an input image. In the method, an overexposed area within the image is determined. The channel values of pixels in the overexposed area are applied with corresponding weights. An automatic white balance process is performed on the channel values of pixels in the overexposed area according to an expectation of low saturation in the overexposed area. Besides a first channel value of each of the pixels, a second channel value and a third channel value of the pixel can be estimated according to the channel values of periphery pixels. A correction value overexposed of the first channel value of the current pixel can be calculated according to the corresponding weights of the pixels in the overexposed area.

Abstract: A method for process control of a semiconductor structure fabricated by a series of fabrication steps, the method comprising obtaining an image of the semiconductor structure indicative of at least two individual fabrication steps; wherein the image is generated by scanning the semiconductor structure with a charged particle beam and collecting signals emanating from the semiconductor structure; and processing, by a hardware processor, the image to determining a parameter of the semiconductor structure, wherein processing includes measuring step/s from among the fabrication steps as an individual feature.

Abstract: This disclosure provides an image processing apparatus comprising a first setting unit which sets a first parameter for processing for removing an influence of a fine particle component based on image data; a first image processing unit which performs fine particle removal processing based on the first parameter; a second setting unit which sets a second parameter; a second image processing unit which performs fine particle removal processing based on the second parameter; a setting unit which sets a region for which the first image processing unit is to be used and a region tor which the second image processing unit is to be used and a generation unit which generates image data by applying a result from the first image processing unit and a result from the second image processing unit to the respective set regions.

Abstract: A system for computer-aided triage includes a router, a remote computing system, and a client application. A method for computer-aided triage includes receiving a data packet associated with a patient and taken at a point of care; checking for a suspected condition associated with the data packet; in an event that the suspected condition is detected, determining a recipient based on the suspected condition; and transmitting information to a device associated with the recipient.

Abstract: Techniques are described for merging super pixels of an image. The image may include two superpixel, for which a similarity value is calculated. The similarity value is determined based on the link and cut values of the superpixels, the similarity value representing pixel-based similarity of the superpixels. The link value is determined based on the similarity between color values of the pixels in the superpixels, while the cut value is determined based on the edge pixels of the superpixels. Based on the calculated similarity value, the system determines whether to merge the superpixels and if so, merges the superpixels thereby generating another superpixel.

Abstract: Disclosed is a system and associated methods for generating and rendering a polyhedral point cloud that represents a scene with multi-faceted primitives. Each multi-faceted primitive stores multiple sets of values that represent different non-positional characteristics that are associated with a particular point in the scene from different angles. For instance, the system generates a multi-faceted primitive for a particular point of the scene that is captured in first capture from a first position and a second capture from a different second position.

Abstract: An image debanding method includes selecting a first and a second comparison pixel from a plurality of adjacent pixels within a preset pixel distance range in a straight pixel direction according to each of the plurality of adjacent pixels and the to-be-compensated pixel; calculating a first compensation value according to a first difference between pre-debanding color values of the first comparison pixel and the to-be-compensated pixel, a first pixel distance between the first comparison pixel and the to-be-compensated pixel, and the preset pixel distance range; calculating a second compensation value according to a second difference between the pre-debanding color values of the second comparison pixel and the to-be-compensated pixel, a second pixel distance between the second comparison pixel and the to-be-compensated pixel, and the preset pixel distance range; and calculating a post-debanding color component value of the to-be-compensated pixel.

Abstract: Embodiments relate to a method and system for determining a situation of a facility by imaging a sensing data of the facility including receiving sensing data through a plurality of sensors at a query time, generating a situation image at the query time, showing the situation of the facility at the query time based on the sensing data, and determining if an abnormal situation occurred at the query time by applying the situation image to a pre-learned situation determination model.

Abstract: In implementations of image content snapping guidelines, a guidelines segmentation system includes modules, such as an image pre-processing module to reduce the image size of a digital image if the image size exceeds an image size threshold. An object segmentation module segments objects depicted in the digital image and identifies each object by a bounding border that delineates an object region boundary. An edge detection module receives a segmented object and determines object external edges and object feature edges from the segmented object, and identifies object corners of the object. A snapping guidelines module determines image content snapping guidelines of an object depicted in the digital image, the image content snapping guidelines for an object determined based on the bounding border of the object region boundary, the object external edges, the object feature edges, and projected snapping guidelines that extend from the object corners of the object.

Abstract: An improved method for examining an article by using a vision system is presented. Also presented is a vision system for use within such a method.

Abstract: Disclosed herein are a visual story generation method and apparatus for generating a story from a plurality of images by using a deep learning network. The visual story generation method includes: extracting features from a plurality of respective images by using the first extraction unit of a deep learning network; generating the structure of a story based on the overall feature of the plurality of images by using the second extraction unit of the deep learning network; and generating the story by using outputs of the first and second extraction units.

Abstract: A first image including a first line segment is projected onto a projection surface to acquire first imaging data of a first projected image. A second image including a first mark and a second mark overlapping the first line segment is projected onto the projection surface to acquire second imaging data of a second projected image. Based on a positional relation between a third mark and a fourth mark located on a second line segment corresponding to the first line segment and a positional relation between the first mark and the second mark located on the first line segment, relation data that associates the first mark and the third mark and associates the second mark and the fourth mark is generated. Correction data is generated based on the relation data. Image data is corrected based on the correction data. A corrected image is projected onto the projection surface.

Abstract: A screen coding method and system based on mass center coincidence. The screen coding method based on mass center coincidence includes: constructing a plurality of coding unit models composed of a combination of a plurality of geometric figures with coincident mass centers, where vertices of the geometric figures do not coincide; and filling in data information to each vertex of the coding unit models according to a method of data information arrangement of a plurality of data combinations to generate a coding unit so as to implement different data lengths of the same coding unit. As such, a data length of the coding unit can be controlled, so that when more data needs to be coded, the overall size of the coding unit does not need to be changed, which greatly improves coding efficiency.

Abstract: An image processing device includes an input device which receives image adjustment selections from an associated user interface device. Memory of the device stores a user interface generator, which generates a background adjustment selector for presenting to a user on the user interface device; a background adjustment component which, for each of a plurality of pixels of an input image computes adjusted color values, as a function of at least one of: (a) a background adjustment factor computed for the respective pixel, and (b) a background class derived from the computed background adjustment factor, the background adjustment factor being a function of a background strength of the pixel and a luminance strength of the pixel; and an image output component outputs an output image derived from the adjusted color values for the plurality of pixels. A processor implements the background adjustment component and image output component.

Abstract: Systems and methods for displaying super saturated color. Image data for display on a display or viewing device with a potential white luminance in a standard system with a maximum luminance is processed such that colors near the white point are reduced to a limited luminance. As the chroma of the displayed color is increased, a luminance attenuation is decreased. The scaling of the reduction is operable to be a linear function, a non-linear function, or any other function.