Abstract: A computer-implemented method for the ordinal classification of at least one microscope image calculates a classification into one of a plurality of classes which form an order with respect to an image property. The microscope image is input into a machine-learned model for ordinal classification. The model comprises binary classifiers which calculate estimates regarding whether the microscope image belongs to cumulative auxiliary classes, which combine different numbers of the classes which follow each other in the order. The estimates can be combined so as to form a total score, wherein the classification occurs by comparing the total score with threshold values which can be defined in a variable manner depending on the application, or interval limits of the classes can be defined so that the classes form intervals of different widths. The model for ordinal classification can also comprise further binary classifiers for inverse auxiliary classes.

Abstract: One example method includes receiving a digital image, receiving an input list that includes a respective hash for each frame in a group of frames, creating new frames on a particular area of the digital image, and the new frames are created and located based on the information in the input list, obtaining a respective hash for content included within each of the new frames, comparing one of the hashes generated for one of the new frames with a hash from the input list and, when the hashes match, continue the comparing for all frames of the particular area, and when all hashes from the input list have been checked, determining whether or not the digital image is an illegal image.

Abstract: A system and method for extracting a full range hyperspectral data from one or more RGB images. The method encompasses pre-processing, the one or more RGB images. Further the method encompasses estimating, an illumination component associated with each pre-processed RGB image. The method thereafter comprises removing, the illumination component from the each pre-processed RGB image. Further the method encompasses tracking, a trajectory of pixel(s) over frame(s) associated with the each pre-processed RGB image. The method then leads to identifying, a position of the pixel(s) in one or more adjacent frames of the frame(s) based on a patch defined around said one or more pixels. Thereafter the method encompasses extracting, the full range hyperspectral data from the each pre-processed RGB image based on at least one of the removal of the illumination component, the trajectory of the pixel(s) and the position of the pixel(s).

Abstract: A method for enhancing images for metrological applications. A first set of first images is provided, wherein the first set comprises at least one first image, the first set representing a scene of interest, and a second set of second images is provided, wherein the second set comprises at least one second image, the second set representing at least a part of the scene of interest. The method comprises the following steps: 1) jointly processing the first set and the second set by a neural network, and 2) outputting a third set of images by the neural network, the third set comprising at least one processed image, from which is determinable the position and/or orientation of the at least one object with a processed precision, wherein the processed precision is equal to or higher than the initial precision.

Abstract: A portion of a polygon is appropriately extracted from an image.

Abstract: A driving assistance device that recognizes a lane marking around an own vehicle with at least one sensor includes a lane marking detection unit that detects lane marking information from data acquired by the sensor, a lane marking type candidate estimation unit that recognizes a lane marking type from the detected lane marking information and calculates a likelihood of each lane marking type, a lane marking type branch point estimation unit that detects a lane marking type branch point that is a point at which a likelihood of the lane marking type changes with respect to an advancing direction of the own vehicle, and distinguishes regions before and after the lane marking type branch point as a first region and a second region, and a lane marking information integration unit that, in a case where a lane marking of the first region and a lane marking of the second region have the same lane marking type, integrates the lane marking of the first region and the lane marking of the second region into a continuous

Abstract: According to at least one embodiment, a multi-angle multi-time-point method authenticates 2D objects with high confidence by sampling the object through space and time while being capable of automatically authenticating and inputting object information. Some embodiments further enhance authentication confidence by utilizing unique characteristics of hologram and/or personal photo. While this method possesses artificial intelligence comparable to human's in term of authenticating and extracting information from 2D objects, it's also highly efficient and can achieve real-time performance (e.g., processing 5 frames per second) on ordinary personal computers. Structural information is first extracted from a 2D image to reduce processing time for subsequent steps as more operations on the 2D images are avoided. By employing similar divide-and-conquer strategy according to a binary search algorithm for 1D data array, a Visual Binary Edge Search Algorithm is applied to a 2D image application.

Abstract: Some embodiments provide systems comprising: a machine learning model database; a deblur system configured to receive at least a portion of an image comprising a presumed location label captured by the image capture device, and apply at least a deblurring machine learning framework to generate a deblurred label image comprising the presumed location label; a rectification system configured to apply an machine learning transform algorithm to the deblurred label image to generate a rectified label image; an optical character recognition (OCR) system configured to apply a recognition machine learning model to the rectified label image to estimate text; and a location estimation system configured to estimate a location of the presumed location label as a function of the estimated text of the presumed location label relative to known text on known location labels position at respective different known locations within the product storage facility.

Abstract: Real world object reconstruction and representation include performing operations that include sampling locations along a camera ray from a virtual camera to a target object to obtain a sample set of the locations along the camera ray. For each location of the at least a subset of the sample set, the operations include determining a position of the location with respect to the target object, executing, based on the position, a reflectance multilayer perceptron (MLP) model, to determine an albedo and material shininess for the location, and computing a radiance for the location and based on a viewing direction of the camera ray using the albedo and the material shininess. The operations further includes rendering a color value for the camera ray by compositing the radiance across the first sample set.

Abstract: A method for inspecting an object includes determining a first inspection package that includes a first inspection image of the object and a first designation. The method includes determining data indicative of a second inspection package that includes a second inspection image of the object and a second designation. The method includes determining a first property of the object based on the first inspection image of the object, one or more properties maps of the object, and the first designation. The method includes determining a second property of the object based on the second inspection image of the object, the one or more properties maps of the object, and the second designation. The method includes displaying the first property and the second property or displaying data indicative of a comparison of the first property with the second property.

Abstract: Disclosed embodiments may include a system for identifying a statement. This may include receiving document image data which is then processed using optical character recognition to create language data and position data. The system may include identifying a plurality of dates from the language data and determining whether the plurality of dates is aligned in a first direction using the position data. The system may include determining whether the plurality of dates is within a predetermined time threshold or counting the plurality of dates to determine whether the count is greater than a predetermined count threshold. The system may create a label for the document and generate and transmit a graphical user interface to a user device for displaying the label and/or the document image data. The user may be able to interact with the user device to change the document label.

Abstract: A method of image enhancement, the method comprising: obtaining image data representing an image comprising a plurality of pixels, each having a pixel intensity value, the image further comprising a region of interest; analyzing image data associated with the region of interest and gathering relevant statistics thereon; analyzing image data associated with the image as a whole and gathering relevant statistics thereon; accumulating a histogram based on the intensity value of pixels in the image as a whole; defining histogram bins of interest that correspond to a range of pixel intensity values from within the region of interest; attenuating histogram bins outside of the bins of interest OR multiplying bins of interest by a scaling factor; using the attenuated or scaled histogram to create a cumulative distribution function; and using the cumulative distribution function to produce a contrast enhanced image.

Abstract: A method for tracking a movable implement of a work vehicle. The method comprises the steps of 1.) accessing images during movement of the work vehicle providing a view onto an environment and at least part of the implement, 2.) providing by a feature tracking algorithm a 3D environment model and referencing of the sensor pose to the 3D environment model, 3.) tracking implement features at different poses of the implement and, determining implement tracking data providing positional and arrangement information for the implement features, 4.) accessing benchmark information providing a real distance between two benchmark points, 5.) using the benchmark information to provide the implement tracking data with absolute scale information, and 6.) using the implement tracking data for the tracking of the implement.

Abstract: An operation method of a wafer analysis device include: generating a wafer map that is an image visualizing and showing whether each of a plurality of chips included in a wafer is normal or defective; applying virtual normal chips to the wafer map such that the number of chips adjacent to each of all the chips on an outermost edge of the wafer map is eight; obtaining the number of normal chips among eight adjacent chips of each of defective chips among the plurality of chips; determining whether a failure of each of the defective chips is caused by a systematic failure or a random failure.

Abstract: Provided is a method for training a content moderation mode. The method includes extracting part of image data of a sample video file as sample image data; positioning a time point of the sample image data in the sample video file in the case that the sample image data contains offensive content; extracting salient image region data from the image data around the time point; and training the content moderation model based on the image region data and the sample image data.

Abstract: A method for determining a position of an image capture device (ICD) within a building site, the module comprising: registering an image captured in the building site by the ICD; registering an initial ICD position of the ICD at the time the image was captured; generating a plurality of proposed ICD positions based on the initial ICD position; and selecting an optimized ICD position from the plurality of proposed ICD positions. Optionally, the optimized ICD position is selected responsive to a model of the building site that comprises sufficient information to generate a three dimensional (3D) representation of the building site.

Abstract: Disclosed herein method and apparatus for detecting changes between heterogeneous image data for identifying disaster damage. The method includes obtaining observation image data of an event occurrence region and reference image data that occurs before an event and has a heterogeneous type of an image from the observation image data; processing the observation image data and the reference image data according to an attribute of the observation image data and preprocessing the observation image data and the reference image data to determine whether or not there is an exceptional object to be excluded from a change analysis in the processed observation image data and the processed reference image data based on an event type and to process the exceptional object; and detecting a change area of the event occurrence region based on the preprocessed observation image data and the preprocessed reference image data.

Abstract: A system for generating a scanning list of objects to be scanned for creating an image data set for use in object detection training. A list of the objects to be scanned is received. An initial set of object combinations of the objects to be scanned is enumerated. A modified set of object combinations is generated by applying rules to each object combination in the initial set of object combinations, the rules including identifying known objects based on inclusion of other objects in the combination, and the rules including identifying unscannable objects based on inclusion of other objects in the combination. The scanning list is generated by selecting object combinations from the modified set of object combinations until all objects to be scanned appear at least once in the scanning list.

Abstract: Systems and methods for slide image alignment are described herein. An example method includes receiving a plurality of slide images, detecting a plurality of features contained in the slide images, and comparing a plurality of pairs of the slide images. The comparison uses the detected features. The method also includes creating a distance matrix that reflects a respective difference between each of the pairs of the slide images, creating a graph by connecting each of the slide images to its most similar slide image, and detecting a plurality of graph components. Each of the graph components includes one or more of the slide images. The method further includes aligning the slide images within each of the graph components, and aligning the graph components to form a composite image.

Abstract: State of the art mechanisms being used for achieving diagnostic-quality images under low-dose settings for general CT imaging have the disadvantages that CT images are fixed during the optimization process to generate perfusion maps, which can lead to suboptimal CT images with respect to the perfusion maps generated, although they might appear spatially smooth or denoised. The disclosure herein generally relates to Computer Tomography (CT) scanning, and, more particularly, to a method and system for CT image reconstruction. The system performs modelling an optimization problem for joint estimation of a set of structural CT images and a perfusion map, and further solves the optimization problem for the reconstruction of the CT images of a subject.