Abstract: A color tone correction system includes a reception unit that receives a target workpiece image and design information of a target workpiece, a reference image data storage unit that stores a reference workpiece image, an image determination unit that determines whether or not the target workpiece is inclined more than the reference workpiece, a calculation processing unit that estimates an inclination angle of the target workpiece based on the stored reference workpiece image and the target workpiece image, a color tone data storage unit that stores a relationship between the inclination angle and a color tone correction value, an image correction unit that corrects a color tone of the target workpiece image based on the estimated inclination angle and a color tone correction formula corresponding to the stored relationship, and an output unit that outputs the corrected target workpiece image.

Abstract: Systems and methods for training machine learning models based on domain constraints are disclosed. An example method includes receiving a plurality of images, each image associated with a cluster of a plurality of clusters, the plurality of clusters representing an output of a second machine learning model, assigning a label to each cluster of the plurality of clusters based at least in part on a plurality of constraints, identifying, based at least in part on the plurality of constraints, a first label mismatch for a first image, the first label mismatch indicating that the first image belongs to a first cluster but should be assigned to a second cluster different from the first cluster, reassigning the first image to the second cluster, and training the first machine learning model, based on the labeled clusters of the plurality of clusters, to predict labels associated with subsequently received image data.

Abstract: Disclosed is a system and method for operating an imaging system. The imaging system may move or be moved to acquire image data of a subject at different positions relative to the subject. The image data may, thereafter, be combined to form a single image.

Abstract: The present disclosure describes a computer-implemented method of transforming a low-resolution MR image to a high-resolution MR image using a deep CNN-based MRI SR network and a computer-implemented method of transforming an MR image to a pseudo-CT (sCT) image using a deep CNN-based sCT network. The present disclosure further describes a MR image-guided radiation treatment system that includes a computing device to implement the MRI SR and CT networks and to produce a radiation plan based in the resulting high resolution MR images and sCT images.

Abstract: Disclosed is a video stabilization method including steps of selecting a first area in a first image; determining at least one first feature point based on the first area, and performing feature point matching on the first image and a second image so as to obtain at least one feature point matching pair between the first image and the second image, each feature point matching pair including a first feature point of the first image and a second feature point of the second image; conducting motion parameter estimation based on the at least one feature point matching pair so as to obtain a motion parameter; and carrying out motion compensation with respect to the first image based on the motion parameter so as to acquire a first stable image after compensation.

Abstract: The disclosure provides an answer correction method and a device, including: determining the target test paper that matches the test paper to be corrected; marking the area of each answer in the test paper to be corrected as the first answer set, and marking the area of each answer in the target test paper as the second answer set; matching each answer area in the first answer set and the second answer set, and adjusting the position of the answer area in the first answer set on the test paper to be corrected; for each answer area in the second answer set, determining the target answer area in the first answer set according to the position information of the answer area on the target test paper, and correcting the answer in the determined target answer area according to the answer in the answer area. The disclosure can solve the problem in the related art that the accurate position of the answer filled by the student cannot be identified, thereby affecting the correction of the answer.

Abstract: A image of a target is obtained and processed to find changes in the target which represent projectiles hitting the target, and that target is then scored.

Abstract: Embodiments of the invention provide a laser system including a laser station including at least one laser, at least one processor, and at least one non-transitory computer-readable storage medium in data communication with the at least one processor. The at least one non-transitory computer-readable storage medium includes program instructions executable by the at least one processor, and enabling or operating an exchange of data between the at least one laser station and at least one remote network. The laser system includes at least one GUI display configured and arranged to display operating parameters or functions of the at least one laser and/or any of the data exchanged between the laser station and at least one remote network. The program instructions include instructions that direct the processor to update the at least one GUI display with a plurality of user-selectable graphics arranged around the periphery or circumference of a central display.

Abstract: Methods for characterizing fluids from a patient. A time series of images of a conduit are received, and a conduit image region in the images is identified. A flow type of the fluids passing through the conduit may be classified as one of air, laminar liquid, and turbulent liquid by evaluating an air-liquid boundary of the fluid. A volumetric flow rate of the fluids in the conduit is estimated. The volumetric flow rate may be based on the classified flow type. A concentration of a blood component of the fluids passing through the conduit may be estimated based on the images. A proportion of the fluid that is blood may also be determined, and a volume of blood that has passed through the conduit within a predetermined period of time may be estimated based on the estimated total volumetric flow rate and the determined proportion.

Abstract: A liveness test method and apparatus is disclosed. The liveness test method includes detecting a face region in an input image for a test target, implementing a first liveness test to determine a first liveness value based on a first image corresponding to the detected face region, implementing a second liveness test to determine a second liveness value based on a second image corresponding to a partial face region of the detected face region, implementing a third liveness test to determine a third liveness value based on an entirety of the input image or a full region of the input image that includes the detected face region and a region beyond the detected face region, and determining a result of the liveness test based on the first liveness value, the second liveness value, and the third liveness value.

Abstract: A computer-implemented method and system for processing a document page is based on text and non-text detections in an image path. An object block is generated for each image content identified within an input page. the blocks are extracted from the input document for downstream processing. Then, the object blocks are classified based on whether the content is text or non-text. The extracted non-text objects—which are specified by their bounding boxes—are processed separately from the rest of the content. The processing is performed on the text content blocks in parallel. However, when error diffusion is employed, the error diffusion is performed sequentially on the non-text content blocks to avoid stitching artifacts between individually error diffused patches in non-text areas.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed to detect unconfined view media. A disclosed apparatus includes means for generating a pixel map to generate a reference pixel map for media data; means for detecting a field of view to detect a field of view for a presentation of the media data; and means for determining a view edge to determine a first view edge based on the field of view and the reference pixel map and that the media data corresponds to unconfined view media based on the first view edge.

Abstract: A structural analysis computing device may generate a proposed insurance claim and/or generate a proposed insurance quote for an object pictured in a three-dimensional (3D) image. The structural analysis computing device may be coupled to a drone configured to capture exterior images of the object. The structural analysis computing device may include a memory, a user interface, an object sensor configured to capture the 3D image, and a processor in communication with the memory and the object sensor. The processor may access the 3D image including the object, and analyze the 3D images to identify features of the object—such as by inputting the 3D image into a trained machine learning or pattern recognition program. The processor may generate a proposed claim form for a damaged object and/or a proposed quote for an uninsured object, and display the form to a user for their review and/or approval.

Abstract: A secondary detection system for integrating automated optical inspection and neural network and a method thereof are disclosed. In the secondary detection system, an automated optical inspection apparatus performs automated optical inspection for pin solder joints on circuit board, and when a detection result indicates abnormal condition, the secondary detection device calculates a detection image probability value based on the component image feature and the template image feature, and calculate pin solder joint image probability values based on the component pin solder joint image feature and the template pin solder joint image feature through siamese neural network, to obtain a minimum probability value among the detection image probability value and pin solder joint image probability values. The minimum probability value is used to determine whether to change the detection result, thereby providing accurate detection result of automated optical inspection and increasing a first pass yield.

Abstract: A method, apparatus, electronic device, and storage medium for character recognition are provided. The method may perform image processing on an acquired original image to obtain a region to be recognized. The region may include a character. The method may determine an area ratio of the region to be recognized on the original image. The method may determine an angle between the region to be recognized and a preset direction. The method may determine a character density of the region to be recognized. The method may perform character recognition on the character in the region to be recognized in response to determining that the area ratio is greater than a ratio threshold, the angle is less than an angle threshold, and the character density is less than a density threshold.

Abstract: A framework in which annotated images can be analyzed in small batches to learn and distinguish between higher-quality annotations and lower-quality annotations, especially in the case of manual annotations for which quality assurance is desired. This framework is extremely generalizable and can be used for indoor images, outdoor images, medical images, etc., without limitation. An echo state network (ESN) is provided as a special case of semantic segmentation model that can be trained using as few as tens of annotated images to predict semantic regions and provide metrics that can be used to distinguish between higher-quality annotations and lower-quality annotations.

Abstract: A method for generating and updating position distribution graph comprises: generating a position distribution graph according to a circuit bitmap and an exposure pattern, performing an exposure simulation according to the position distribution graph to generate an exposure result graph, comparing the circuit bitmap with the exposure result graph to generate a plurality of error distribution candidate graphs, selecting one of the error distribution candidate graphs to serve as an error distribution graph, and performing a zero-one integer programming to update the position distribution graph according to the circuit bitmap and the error distribution graph, wherein the updated position distribution graph is associated with the error distribution graph.

Abstract: A liveness test method and apparatus is disclosed. The liveness test method includes detecting a face region in an input image for a test target, implementing a first liveness test to determine a first liveness value based on a first image corresponding to the detected face region, implementing a second liveness test to determine a second liveness value based on a second image corresponding to a partial face region of the detected face region, implementing a third liveness test to determine a third liveness value based on an entirety of the input image or a full region of the input image that includes the detected face region and a region beyond the detected face region, and determining a result of the liveness test based on the first liveness value, the second liveness value, and the third liveness value.

Abstract: A vehicular trailer hitching assist system includes a camera disposed at a rear portion of a vehicle and having a field of view exterior of the vehicle, the field of view encompassing at least a portion of a trailer rearward of the vehicle. The camera captures image data representative of the trailer rearward of the vehicle. A control includes a processor operable to process image data captured by the camera. The control, responsive to processing of image data captured by the camera, detects a trailer hitch coupler of the trailer rearward of the vehicle. The control, responsive to detecting the trailer hitch coupler, estimates an initial height and an initial location of the detected trailer hitch coupler. The ECU tracks the position of the trailer hitch coupler in subsequent frames and the ECU selects a current frame and a previous frame of captured image data to refine the initial height.

Abstract: A structural analysis computing device may generate a proposed insurance claim and/or generate a proposed insurance quote for an object pictured in a three-dimensional (3D) image. The structural analysis computing device may be coupled to a drone configured to capture exterior images of the object. The structural analysis computing device may include a memory, a user interface, an object sensor configured to capture the 3D image, and a processor in communication with the memory and the object sensor. The processor may access the 3D image including the object, and analyze the 3D images to identify features of the object—such as by inputting the 3D image into a trained machine learning or pattern recognition program. The processor may generate a proposed claim form for a damaged object and/or a proposed quote for an uninsured object, and display the form to a user for their review and/or approval.