Abstract: Systems and methods are disclosed for receiving a target image corresponding to a target specimen, the target specimen comprising a tissue sample of a patient, applying a machine learning model to the target image to determine at least one characteristic of the target specimen and/or at least one characteristic of the target image, the machine learning model having been generated by processing a plurality of training images to predict at least one characteristic, the training images comprising images of human tissue and/or images that are algorithmically generated, and outputting the at least one characteristic of the target specimen and/or the at least one characteristic of the target image.

Abstract: This disclosure provides techniques for assessing quality of a deposited film layer of an organic light emitting diode (“OLED”) device. An image is captured and filtered to identify a deposited layer that is to be analyzed. Image data representing this layer can be optionally converted to brightness (grayscale) data. A gradient function is then applied to emphasize discontinuities in the deposited layer. Discontinuities are then compared to one or more thresholds and used to ascertain quality of the deposited layer, with optional remedial measures then being applied. The disclosed techniques can be applied in situ, to quickly identify potential defects such as delamination before ensuing manufacturing steps are applied. In optional embodiments, remedial measures can be taken dependent on whether defects are determined to exist.

Abstract: Detection and analysis of a tangible component in a sample are implemented at lower cost. Provided is an analysis apparatus including a flow cell which includes a flow path for a sample, a branch section configured to cause light having passed through the flow path to branch at least to a first optical path and a second optical path, a first imaging section and a second imaging section configured to capture images of the sample in the flow path by using the light in the first optical path and the light in the second optical path, and a controller configured to process the captured images. The first imaging section and the second imaging section capture images that have the same angle of view but have different characteristics.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for creating user interface control images for robotic automation. One of the methods includes detecting, during a training process, a control selection event; retrieving a first image and a second image; determining a difference image that represents a difference between the first image and the second image; determining, using the difference image, a plurality of colors for pixels included in the difference image that are likely located outside of a control location for the control; determining one or more shapes depicted in the difference image that each have a color other than all of the colors in the plurality of colors; selecting, from the one or more shapes and using an event location, a particular shape as likely representing the control; and storing a cropped image of the control extracted from one of the two or more images.

Abstract: A parking enforcement system includes an autonomous vehicle that is equipped with an image capture device that is configured to capture images of license plates of parked vehicles while the autonomous vehicle moves through a parking zone. The system will process the images to extract license plate numbers from the images. The system will correlate the license plate numbers with data in a parking enforcement database to determine whether the license plate numbers are associated with an unexpired parking transaction. For any license plate number that is not subject to an unexpired parking transaction, the system may initiate an enforcement action. For any license plate number that is subject to an unexpired parking transaction, the system may not initiate an enforcement action.

Abstract: At least one contemporaneous signature image is captured while a user generates an electronic signature for a document. When one or more contemporaneous signature images maps to a verification image, signature data representative of an electronic signature is associated with the document.

Abstract: A method and a system for determining a center of resistance point of a tooth for orthodontic treatment planning are provided. The method comprises: obtaining a tooth mesh from image data associated with a tooth crown of a patient; identifying a mesiodistal center of the tooth crown; determining a reference plane in the image data to extend through the mesiodistal center; determining an intersection curve based on an intersection of the reference plane and the tooth mesh, the intersection curve following a shape of the surface of the crown at the reference plane; determining a tooth axis of the tooth crown based on the intersection curve; determining a crown height of the tooth crown based on the tooth axis; and determining the center of resistance of the tooth based on the determined crown height and the determined tooth axis.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for receiving user input for an object classification of interest for image data (e.g. single frame image, continuous video, etc.) from a user device, and for each object specified by identified object data to belong to the object classification of interest, displaying data that presents each object and/or text block of interest on a user device.

Abstract: A vehicle that includes one or more sensors configured to output data and an electronic control unit. The electronic control unit is configured to receive first data from the one or more sensors at a first time, detect an object based on the first data received from the one or more sensors at the first time, classify the object into a classification based on the first data received from the one or more sensors at the first time, and receive second data from the one or more sensors at a second time. The second time is subsequent to the first time. The electronic control unit is further configured to select a proper subset of the second data for further processing based on the classification of the object, and track the object based on the proper subset of the second data selected for further processing.

Abstract: The described implementations relate to systems, methods, and apparatuses for generating regions of interest (214) from imaging data (212). Specifically, the regions of interest are generated for tracking treatment efficacy in a more consistent and repeatable manner. The regions of interest can be generated from contrast medium and non-contrast medium enhanced scans (102) of a patient. Voxel data derived from the scans can be collected and distributed according to respective intensity values in order to identify mode voxels (116, 118, 120) for particular ranges (128) of intensities. Regions of interest (110, 112, 114) can then be generated for each identified mode voxel, and standard deviations for the regions of interest can be determined. One or more thresholds can be derived from the determined standard deviations in order to further filter the intensity values and identify filtered groups of voxels to be the resulting regions of interest.

Abstract: Provided is a road obstacle detection method including: a region segmentation step of segmenting an input image into a plurality of local regions; and a likelihood calculation step of calculating a probability of presence of the road obstacle in a target local region based on a probability that the target local region is not a normal object set in advance and a degree of visual saliency defined by a relationship between a surrounding local region and the target local region, wherein the degree of the visual saliency is calculated to be larger as a probability that the surrounding local region is a road is higher and calculated to be larger as a difference in visual characteristics between the target local region and the surrounding local region is larger.

Abstract: A method for processing an optical image acquired by a space vehicle or an aerial vehicle having a ground reflectance model and an atmospheric model, the atmospheric model having an aerosol model and a cloud model; determining optimal values of atmospheric model parameters to optimise the atmospheric model with respect to the image; determining correction parameter values for each layer of the atmospheric model, converting the image into a ground image with environmental effects according to the correction parameter values, converting the ground image with environmental effects into a ground image with no environmental effects according to the correction parameter values.

Abstract: Techniques for intelligent coalescing of media streams are described. A coalesce engine receives multiple media streams, such as audio or video streams, that are misaligned. The coalesce engine can analyze the media streams by comparing representations of elements of the media streams to detect the misalignment. The coalesce engine may determine an offset amount representing the misalignment, and if the offset amount meets or exceeds a threshold the coalesce engine can work to eliminate the misalignment by introducing one or more artificial delays before sending elements of ones of the media streams that are “ahead” of others of the streams. The coalese engine can additionally or alternatively send feedback to sources of the media streams, causing the source(s) to attempt to mitigate the misalignment.

Abstract: An approach is provided for an asymmetric evaluation of polygon similarity. The approach, for instance, involves receiving a first polygon representing an object depicted in an image. The approach also involves generating a transformation of the image comprising image elements whose values are based on a respective distance that each image element is from a nearest image element located on a first boundary of the first polygon. The approach further involves determining a subset of the plurality of image elements of the transformation that intersect with a second boundary of a second polygon. The approach further involves calculating a polygon similarity of the second polygon with respect the first polygon based on the values of the subset of image elements normalized to a length of the second boundary of the second polygon.

Abstract: The present application relates to a method and system for analyzing blood flow conditions. The method includes: obtaining images at multiple time phases; constructing multiple vascular models corresponding to the multiple time phases; correlating the multiple vascular models; setting boundary conditions of the multiple vascular models respectively based on the result of correlation; and determining condition of blood vessel of the vascular models.

Abstract: The present disclosure provides apparatus and methods for automated tracking and counting of objects in a set of image frames using a resource-constrained device based on analysis of a selected subset of image frames, and based on selectively timing when resource-intensive operations are performed.

Abstract: An image processing apparatus includes an information obtaining unit configured to obtain three-dimensional polarization sensitive tomographic information and three-dimensional motion contrast information about a subject based on tomographic signals of lights having different polarizations, the lights being obtained by splitting a combined light obtained by combining a returned light from the subject illuminated with a measurement light with a reference light corresponding to the measurement light, an obtaining unit configured to obtain a lesion region of the subject using the three-dimensional polarization sensitive tomographic information, and an image generation unit configured to generate an image in which the lesion region is superimposed on a motion contrast image generated using the three-dimensional motion contrast information.

Abstract: A method is disclosed including: receiving raw image data corresponding to a series of raw images; processing the raw image data with an encoder to generate encoded data, where the encoder is characterized by an input/output transformation that substantially mimics the input/output transformation of one or more retinal cells of a vertebrate retina; and applying a first machine vision algorithm to data generated based at least in part on the encoded data.

Abstract: Each of vehicles acquires its own position, and transmits an image of a nearby outside taken by an own camera and a piece of information of the own position. An information center communicatable wirelessly with the vehicles receives the images and the pieces of information of the vehicles' positions transmitted by the vehicles, and recognizes pieces of first character information appearing in the received images, respectively. Based on the received pieces of information of the vehicles' positions as well as at least either points of interest or areas stored as collection target information, the information center determines at least either points of interest or areas for the recognized pieces of first character information, respectively, and stores association information where the pieces of first character information are associated with the determined at least either points of interest or areas.

Abstract: A tracking device includes: an imaging unit that inputs an image into an image input unit; a first moving body detection unit that calculates an optical flow and detects a position and a direction of movement of a moving body based on the calculated optical flow; a second moving body detection unit that detects a position and a direction of movement based on a plurality of overhead images generated; a third moving body detection unit that detects a position and a direction of movement by integrating detection results from the first and second moving body detection units; a tracked moving body confirmation unit that determines a moving body to be tracked based on detection results from the first to third moving body detection units; an estimation unit that estimates a future position and direction of movement; and a tracking unit that tracks the tracked moving body and identifies a position.