An image acquisition method includes defining a first optical sensor configuration of a matrix to acquire the image of a first celestial body of first nature, the first configuration having a plurality of unit pixels, defining at least one second optical sensor configuration of the matrix to acquire the image of the second celestial body of second nature, the second configuration having a plurality of macro-pixels formed by groupings of unit pixels, and selecting one of the optical sensor configurations, the selection being made according to the nature of the observed celestial body.

A method includes patterning a hard mask over a target layer, capturing a low resolution image of the hard mask, and enhancing the low resolution image of the hard mask with a first machine learning model to produce an enhanced image of the hard mask. The method further includes analyzing the enhanced image of the hard mask with a second machine learning model to determine whether the target layer has defects.

Some example embodiments relate to a super resolution scanning electron microscope (SEM) image implementing device and/or a method thereof. Provided a super resolution scanning electron microscope (SEM) image implementing device comprising a processor configured to crop a low resolution SEM image to generate a first cropped image and a second cropped image, to upscale the first cropped image and the second cropped image to generate a first upscaled image and a second upscaled image, and to cancel noise from the first upscaled image and the second upscaled image to generate a first noise canceled image and a second noise canceled image.

Provided is a processing apparatus including a processing unit that is connected to a data bus, and performs control involved with an image which is output by each of a plurality of image sensors connected to the data bus, through the data bus.

An imaging system, comprising a shooting operation interface that operates to form an image of a subject, and a processor that has a bio-information acquisition section and a stress determination section, wherein the bio-information acquisition section acquires bio-information of an operator when, during shooting awaiting action where an instant for acquiring still images is awaited, the shooting operation interface is operated, and the stress determination section determines stress conditions that shooting actions place on the operator based on the bio-information that has been acquired using the bio-information acquisition section.

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.

A contextual local image recognition module of a device retrieves a primary content dataset from a server and then generates and updates a contextual content dataset based on an image captured with the device. The device stores the primary content dataset and the contextual content dataset. The primary content dataset comprises a first set of images and corresponding virtual object models. The contextual content dataset comprises a second set of images and corresponding virtual object models retrieved from the server.

An image capturing apparatus includes a capture part acquiring image data, and a display displaying an image on a display based on the image data. First information acquired includes at least either an azimuth angle or an elevation angle as a direction of the image and at least either an angle of view of the image or angle-of-view related information calculating the angle of view. When a second direction of a second image is included within a range of a first angle of view in a first direction of a first image, the second image is associated with the first image, and the first image is displayed within the display, and display is performed in a state in which the second image to be associated with the first image is overlapped on the first image within the display as the second image or second information indicating the second image.

An automatic measuring system containing configurable integrated circuits is able to process information via captured images. The automatic measuring system includes a metering instrument, a camera, a recognition module, and a localization module. The metering instrument has at least one display for visually displaying a number and measures the amount of measurable substance or resources (i.e., electricity and water) consumed. The camera captures an image of the number representing at least a portion the amount of measurable substance. The recognition module is operable to generate a value in response to the image and the coordinates wherein the coordinates are used to decode the image via restoring captured image to the original readout counter value. The localization module is removably or remotely coupled to the camera and operable to generate the coordinates in accordance with the image captured by the camera.

A system and apparatus for automated image capturing, comprising a microcontroller, an image capturing device operatively coupled to the pair of guiding apparatus using a first electric rotary actuator, a rotary plate operatively mounted on a second electric rotary actuator. The pair of guiding apparatus and the first electric rotary actuator is actuated to cause change in position of the image capturing device relative to an object positioned on the rotary plate and second electric rotary actuator is actuated causing change in angle of orientation of the object positioned on the rotary plate. By varying lighting conditions and for different background images, plurality of images of object are captured using the image capturing device by actuating electro-mechanical components of the apparatus.