The present invention relates to a method for size estimation by image recognition of a specific target using a given scale. First, a reference objected is recognized in an image and the corresponding scale is established. Then the specific target is searched and the size of the specific target is estimated according to the acquired scale.

In a computer-implemented method, one or more digital aerial images of a property of a current or potential policyholder may be received. The digital aerial image(s) may be processed to determine one or more features of the property, including one or more features of a tree. A predicted location of roots of the tree is determined based upon the tree feature(s). The property feature(s) is/are analyzed to determine a risk of damage to a structure located on the property, by analyzing at least the predicted location of roots of the tree to determine a risk of damage to a foundation of the structure. Based at least in part on this risk, a risk output is generated that includes an indication of whether action should be taken to mitigate the risk of damage and/or whether insurance coverage should be offered, and/or includes a measure of the risk of damage.

A computer implemented scheme for a light detection and ranging (LIDAR) system where point cloud feature extraction and segmentation by efficiently is achieved by: (1) data structuring; (2) edge detection; and (3) region growing.

The present disclosure generally pertains to systems and methods for detecting surface conditions using multiple images of different polarizations. A system in accordance with the present disclosure captures images having different polarizations and compares the images to evaluate surface conditions of an area, such as a runway, landing pad, roadway, or taxiway on which a vehicle is expected to land or otherwise travel. In some cases, a surface hazard, such as water, ice, or snow covering a surface of the area, may be detected and identified. Information indicative of the surface conditions may be used to make control decisions for operation of the vehicle.

In one example, a method of generating and delivering environmental data includes receiving a request for requested data corresponding to a first environmental characteristic and a second environmental characteristic. The method includes retrieving a first set of data corresponding to the first environmental characteristic. The method includes retrieving a second set of data corresponding to the second environmental characteristic. The method includes generating an image having a first channel and a second channel. The values of the first channel correspond to the first set of data. The values of the second channel correspond to the second set of data.

A computing system includes at least one processor, and a memory communicatively coupled to the at least one processor. The processor is configured to receive at least two successive radar images of precipitation data, generate a motion vector field using the at least two successive radar images, forecast linear prediction imagery of future precipitation using the motion vector field, and generate corrected output imagery corresponding to the forecasted linear prediction imagery of the future precipitation corrected by a first neural network. In addition, the processor is further configured to receive, by a second neural network, the linear prediction imagery, and one of observed imagery and the corrected output imagery, and distinguish, by the second neural network, between the corrected output imagery and the observed imagery to produce conditioned output imagery. The processor is also configured to display the conditioned output imagery on a display.

A computing device is provided, including a processor configured to receive imaging relevance data for a geographic area. The processor may be further configured to generate, based at least in part on the imaging relevance data, image mask instructions specifying a region of interest included in the geographic area. The processor may be further configured to transmit the image mask instructions to a satellite. The processor may be further configured to receive, from the satellite, filtered satellite image data of the region of interest. One or more deprioritized regions of the geographic area outside the region of interest may be excluded from the filtered satellite image data.

A method is provided for locating an image recording of an object such as a celestial body, recorded by at least one imaging recording device from a distance. The method includes acquiring image data which represent the image recording and its point in time of recording; acquiring measurement data which represent, for the point in time of recording, a respective measurement signal of at least one sensor device which is arranged in a surface portion of the object; and matching the image data and the measurement data. The method also includes locating the image recording with respect to the object by a determination of a position in the image recording which corresponds to the location of the sensor device on the basis of the matching, and an associating of the location information with this position.

Systems, methods, and computer readable media for performing task assignment, completion, and management within a crowdsourced surveillance platform. A remote server may identify targets for image capture and may assign capture tasks to users based on travel plans of the user. Users may be assigned task to capture image of target locations lying along a travel path. The remote server may aggregate data related to the captured images and use it to update a map and log changes to the target location over time.

An image processing device 100 includes a calculation unit 110 for calculating a solar radiation spectrum in a given area on the ground surface on the basis of an observed image of the area, a solar radiation spectrum component of the area, and the spectrum of a pure substance estimated in the area, and a conversion unit 120 for converting the observed image on the basis of the calculated solar radiation spectrum.