An imaging apparatus, an imaging control method, and an imaging control program are provided. A digital camera includes an imaging element including a first light-receiving region in which a pixel group including focal point detection pixels is arranged and a second light-receiving region in which a pixel group not including the focal point detection pixels is arranged, and a system control unit, in which the system control unit performs a recording imaging control of causing the imaging element to perform imaging in a first exposure time period and a display imaging control of causing the imaging element to perform imaging by setting an exposure time period of the second light-receiving region as the first exposure time period and setting an exposure time period of the first light-receiving region as a second exposure time period.

Embodiments of the present disclosure provide for improved generation and outputting of object identification data indicating object classifications for object representations. Such objects representations may correspond to depictions of objects in images captured using digital holographic microscopy. Some embodiments generate object identification data by comparing object representations in focused image(s) with specially configured annotated focused images, for example using a specially trained neural network or other machine learning model trained based on such annotated focused images. The annotated focused images are generated including a plurality of channels, each associated with a different grayscale focused image at a different target focal length of a range of target focal lengths. In this regard, model(s), algorithm(s), and/or other specially configured implementations may learn the spatial features of particular object representations and associated object identification data. The trained models may be used to perform accurate comparisons with the annotated focused images.

An electronic device is provided. The electronic device includes at least one processor configured to obtain a plurality of first images as per a first frame rate using the camera based on a signal related to image recording and control the camera to perform focusing of a lens included in the camera on at least one of one or more objects in the plurality of first images while obtaining the plurality of first images, provide a first portion of the plurality of first images as a preview through the display, control the camera to lock the focusing on the at least one object, identify a designated event for slow motion recording while obtaining the plurality of first images, based at least in part on the designated event, obtain a plurality of second images as per a second frame rate higher than the first frame rate using the camera focusing-locked on the at least one object, and provide a video related to the at least one object using a second portion of the plurality of first images and at least one of the plurality of second images.

Apparatuses, systems, and methods dynamically model intrinsic parameters of a camera. Methods include: collecting, using a camera having a focus motor, calibration data at a series of discrete focus motor positions; generating, from the calibration data, a set of constant point intrinsic parameters; determining, from the set of constant point intrinsic parameters, a subset of intrinsic parameters to model dynamically; performing, for each intrinsic parameter of the subset of intrinsic parameters, a fit of the point intrinsic parameter values against focus motor positions; generating a model of the intrinsic parameters for the camera based, at least in part, on the fit of the point intrinsic parameter values against the focus motor positions; and determining a position of a fiducial marker within a field of view of the camera based, at least in part, on the model of the intrinsic parameters for the camera.

An optical detection device of detecting a distance relative to a target object includes a substrate, an optical sensor and a processor. The optical sensor is disposed on the substrate and adapted to capture an image about the target object. The processor is disposed on the substrate and electrically connected with the optical sensor. The processor is adapted to mark a first region and a second region within the image for acquiring first quantity of the first region and second quantity of the second region, and compare the first quantity with the second quantity for determining whether the distance is varied to a predefined condition.

A scanning electron microscope (SEM) device includes: an electron beam source configured to emit an electron beam; a lens unit disposed between the electron beam source and a stage configured to seat an object including structures having a pattern is seated, and including a scanning coil, the scanning coil configured to generate an electromagnetic field to provide a lens, and an astigmatism adjuster; and a control unit. The control unit is configured to change a working distance between the lens unit and the object to obtain a plurality of original images, obtain a pattern image, in which the structures appear, and a plurality of kernel images, in which a distribution of the electron beam on the object appears, from the plurality of original images, and control the astigmatism adjuster to adjust the focus and the astigmatism of the lens unit using feature values extracted from the plurality of kernel images.

The invention discloses a powder leakage monitoring device and a powder leakage monitoring method. The powder leakage monitoring device comprises a light field camera, a 3D PTZ and a computer. Wherein, the light field camera records the original light field images of the monitored area; the 3D PTZ under the light field camera adjusts the shooting angle of the light field camera when it rotates according to the set direction; and the computer respectively connects to the light field camera and the 3D PTZ, which generates refocused images corresponding to the original light field images, and determines the spatial coordinates of the powder leakage point and the hazard range of the powder leakage in the monitored area according to the refocused images and the shooting angle. Therefore, the range and accuracy of powder leakage monitoring are both increased by using this invention.

A method includes receiving, by a computing device, device information for a user device and user environment devices; sending, by the computing device, image templates to the user device using the device information; adjusting, by the computing device, device settings on the user device and the user environment devices in response to a selection of an image template of the image templates; receiving, by the computing device, an image from the user device; comparing, by the computing device, the image to a target image; determining, by the computing device, the image is acceptable; and in response to determining the image is acceptable, sending, by the computing device, the acceptable image to a third party.

A first image is captured by the camera, using a first focus setting and a first aperture size. A first protrusion focus measure in a protrusion area of an object in the first image and a first recess focus measure in a recess area of the object in the first image are determined. A second image is captured by the camera, using the first focus setting and a second aperture size, and the object is detected. A second protrusion focus measure and a second recess focus measure are determined in the second image. A protrusion focus difference between the first and second protrusion focus measures, and a recess focus difference between the first and second recess focus measures are calculated. The protrusion focus difference and the recess focus difference are compared and if they differ by less than a predetermined threshold amount, it is determined that the object is fake.

A method for fusing images and apparatus, a storage medium, and a terminal are provided. The method for fusing images includes: obtaining a long-focal image to be fused and a wide-angle image to be fused; detecting feature points of the long-focal image and wide-angle image with a same scale, and matching the feature points to obtain matching feature point pairs; determining a fusion area based on position distributions of the matching feature point pairs; calculating a mapping matrix from the long-focal image to the wide-angle image at least based on coordinates of the matching feature point pairs in the long-focal image and the wide-angle image; and resampling the long-focal image based on the mapping matrix, and fusing the resampled long-focal image and the wide-angle image in the fusion area to obtain a fused image.