Abstract: A non-transitory computer-readable medium encoded with a computer-readable program which, when executed by a processor, will cause a computer to execute a method of authenticating a 3-D object with a 2-D camera, the method including building a pre-determined database. The method additionally includes registering the 3-D object to a storage unit of a device comprising the 2-D camera, thereby creating a registered 3-D model of the 3-D object. Additionally, the method includes authenticating a test 3-D object by comparing the test 3-D object to the registered 3-D model.

Abstract: Computing devices and methods for reading gauges are disclosed. A gauge reading method includes capturing image data corresponding to a captured image of one or more gauges, detecting one or more gauges in the captured image, cropping a detected gauge in the captured image to provide a use image including the detected gauge, and classifying the detected gauge to correlate the detected gauge with a template image. The gauge reading method also includes attempting to perform feature detection rectification on the use image to produce a rectified image of the detected gauge, performing template matching rectification on the use image to produce the rectified image responsive to a failure to perform the feature detection rectification, and estimating a gauge reading responsive to the rectified image. A computing device may implement at least a portion of a gauge reading method.

Abstract: Various techniques are provided for performing automated full-cell segmentation and labeling in immunofluorescent microscopy. These techniques perform membrane segmentation and nuclear seed detection separate and independently from each other, then combine their results to identify cell boundaries. Some embodiments use texture- and kernel-based image processing to perform the method. In some embodiments, the method for obtaining membrane features disclosed herein can be used in conjunction with or separate from the nuclear features. The results can be used for a variety of purposes, including whole-area cell segmentation in fluorescence-based tissue imaging.

Abstract: There is disclosed in the present disclosure a seismic full horizon tracking method, a computer device and a computer-readable storage medium. The method includes: acquiring three-dimensional seismic data; extracting horizon extreme points from the three-dimensional seismic data to construct a sample space; equally dividing the sample space into a plurality of sub-spaces with overlapping portions, and performing a clustering process on the horizon extreme points in each sub-space to obtain horizon fragments corresponding to each horizon of the three-dimensional seismic data; establishing a topological consistency between the horizon fragments; and fusing the horizon fragments corresponding to each horizon of the three-dimensional seismic data based on the topological consistency, to obtain a full horizon tracking result of the three-dimensional seismic data.

Abstract: Methods and systems for image processing are provided. Image data may be obtained. The image data may include a plurality of voxels corresponding to a first plurality of ribs of an object. A first plurality of seed points may be identified for the first plurality of ribs. The first plurality of identified seed points may be labelled to obtain labelled seed points. A connected domain of a target rib of the first plurality of ribs may be determined based on at least one rib segmentation algorithm. A labelled target rib may be obtained by labelling, based on a hit-or-miss operation, the connected domain of the target rib, wherein the hit-or-miss operation may be performed using the labelled seed points to hit the connected domain of the target rib.

Abstract: A method of inspection and an inspection system for the film deposition process for substrates that includes glass and wafer are disclosed. The inspection system includes multiple camera modules positioned in a load lock unit of a process chamber, such as the camera modules that can capture images of the substrate in the load lock. The images are analyzed by a controller of the inspection system to determine the accuracy of robots in handling the substrate, calibration of the robots based on the analysis, and defects in the substrate caused during the handling and deposition process.

Abstract: There is provided a medical observation apparatus including: a determination unit which determines an apparatus to be used based on a captured image for medical use captured by an imaging device; and a display control unit which causes a related image for medical use corresponding to the determined apparatus and the captured image for medical use to be displayed.

Abstract: Disclosed are systems and methods for characterizing corneal shape abnormalities. These methods may be used to differentiate corneas having subclinical keratoconus from other conditions which cause distortion of corneal shape, including warpage of the cornea due to contact lens wear. Also disclosed is classification scheme to aid diagnosis of corneal conditions and thereby guide clinical decision making regarding patient treatment. This classification scheme is based on computed properties of corneal shape, is amenable to automation, and may be implemented in an integrated system or provided in the form of software encoded on a computer-readable medium.

Abstract: One embodiment facilitates recognizing parts of a vehicle. A convolution module is configured to generate a convolution feature map of a vehicle image. A region proposal module is configured to determine, based on the convolution feature map, one or more proposed regions, wherein a respective proposed region corresponds to a target of a respective vehicle part. A classification module is configured to determine a class and a bounding box of a vehicle part corresponding to a proposed region based on a feature of the proposed region. A conditional random field module is configured to optimize classes and bounding boxes of the vehicle parts based on correlated features of the corresponding proposed regions. A reporting module is configured to generate a result which indicates a list including an insurance claim item and corresponding damages based on the optimized classes and bounding boxes of the vehicle parts.

Abstract: Methods for screening, diagnosing, or predicting presence, progression, or treatment effects of a cognitive dysfunction such as dementia based on an analysis of drawing behavior changes by a pre-trained Naïve Bayes method are provided. The methods include steps of obtaining drawing data of at least one image created by a test subject on a digital device and obtaining personal data of the test subject; reconstructing the at least one image based on the drawing data obtained; converting the drawing data to drawing features comprising a plurality of motion features and a plurality of geometric features; and determining probability that the test subject has a cognitive dysfunction based on the drawing features and the personal data by a pre-trained Naïve Bayes method with a greedy variable selection.

Abstract: A machine receives a large image having large image dimensions that exceed memory threshold dimensions. The large image includes metadata. The machine adjusts an orientation and a scaling of the large image based on the metadata. The machine divides the large image into a plurality of image tiles, each image tile having tile dimensions smaller than or equal to the memory threshold dimensions. The machine provides the plurality of image tiles to an artificial neural network. The machine identifies, using the artificial neural network, at least a portion of the target in at least one image tile. The machine identifies the target in the large image based on at least the portion of the target being identified in at least one image tile.

Abstract: An analysis apparatus (100) includes an image acquisition unit (110) and an analysis unit (120). The image acquisition unit (110) acquires image data of a microfossil in a sample collected from a stratum. The analysis unit (120) analyzes the image data acquired by the image acquisition unit (110) using a machine learning result to analyze a taxon or kind of the microfossil in the image data.

Abstract: There is provided a method, a non-transitory computer readable medium, and a system for measuring a pattern. The method can include (a) obtaining an electron image of an area of a sample, the area comprises the pattern, the electron image comprises multiple lines; each line comprises information obtained by moving an electron beam over a scan line; (b) generating a converted image by applying a noise reduction kernel on the electron image, the noise reduction kernel has a width that represents a number of consecutive lines of the electron image; the width is determined based on relationships between analysis results obtained when using noise reduction kernels of different widths; and (c) analyzing the converted image to provide a pattern measurement.

Abstract: A method for imaging a downhole formation. The method includes combining the captured images to generate a partial image of the formation, wherein the partial image includes captured images separated by gaps representing portions of the formation not captured with sensors what were disposed downhole. The method includes locating dips in the formation within the partial image and interpolating the partial image using the located dips within the partial image.

Abstract: A wind flow sensing system for determining a turbulence of wind flow at a set of different altitudes above a terrain is provided. The wind flow sensing system comprises an input interface configured to receive a set of measurements of radial velocities at line-of-site points above the terrain for each of the altitudes for a set of time steps, and a processor configured to estimate velocity fields for each of the altitudes based on data assimilation of the velocity fields, estimate unbiased horizontal velocities at each of the altitudes and for each time step, determine an average of the unbiased horizontal velocities for a period of time including the set of time steps, and determine, at each of the altitudes, a turbulence based on the unbiased horizontal velocities for each time step and the average of the unbiased horizontal velocity.

Abstract: A water stress detection method for tomatoes in a seedling stage based on micro-CT and polarization-hyperspectral imaging multi-feature fusion, comprising: using micro-CT to scan microscopic morphological features such as water stress stomata, spongy body, palisade tissue, cilia, vascular bundle, root volume, main root, and root hair density of tomatoes; using a polarization-hyperspectral imaging system to obtain macroscopic morphological features such as crown width, plant height, and leaf inclination of water stress plants, as well as leaf vein distribution, average gray, and leaf margin shaded area under a water-sensitive wavelength of 1450 nm, and macroscopic morphological features such as polarization states, stock vectors, and Mueller matrix variables of 1450 nm feature images at 0°, 45°, 90°, 135°, and 180° feature polarization angles.

Abstract: Methods and systems are provided for aggregating features in multiple video frames to enhance tissue abnormality detection algorithms, wherein a first detection algorithm identifies an abnormality and aggregates adjacent video frames to create a more complete image for analysis by an artificial intelligence detection algorithm, the aggregation occurring in real time as the medical procedure is being performed.

Abstract: Aspects of the invention include a computer implemented method for simulating visual field test results from structural scans, the method includes processing eye image data to extract visual functioning related features. Additionally, generating a representation of a visual function of the eye that is independent of a visual field test (VFT) configuration. Then generating a simulated VFT configuration specific test result based at least in part on the representation.

Abstract: The systems and methods disclosed herein provide determination of an orientation of a feature towards a reference target. As a non-limiting example, a system consistent with the present disclosure may include a processor, a memory, and a single camera affixed to the ceiling of a room occupied by a person. The system may analyze images from the camera to identify any objects in the room and their locations. Once the system has identified an object and its location, the system may prompt the person to look directly at the object. The camera may then record an image of the user looking at the object. The processor may analyze the image to determine the location of the user's head and, combined with the known location of the object and the known location of the camera, determine the direction that the user is facing. This direction may be treated as a reference value, or “ground truth.” The captured image may be associated with the direction, and the combination may be used as training input into an application.

Abstract: Computer implemented method for detecting a hand gesture of a user, comprising: (a) Receiving sequential logic models each representing a hand gesture. The sequential logic model maps pre-defined hand poses and motions each represented by a hand features record defined by discrete hand values each indicating a state of respective hand feature. (b) Receiving a runtime sequence of runtime hand datasets each defined by discrete hand values scores indicating current state hand features of a user's moving hand which are inferred by analyzing timed images depicting the moving hand. (c) Submitting the runtime hand datasets and the pre-defined hand features records in SSVM functions to generate estimation terms for the runtime hand datasets with respect to the hand features records. (d) Estimating which of the hand gestures best matches the runtime sequence depicted in the timed images by optimizing score functions using the estimation terms for the runtime hand datasets.