A verification apparatus reads an image of a printed sheet using a plurality of imaging units to obtain image data. The verification apparatus extracts feature points of the obtained image data and determines whether a feature point of first image data obtained by a first imaging unit should be a feature point of second image data that should be obtained by another imaging unit. If so, the verification apparatus converts coordinates of the feature point of the second image data to a coordinate system of the first imaging unit, calculates a geometrical conversion parameter from the coordinates of the converted feature point and coordinates of feature points other than the converted feature point, and aligns the image data of the printed sheet and a correct image based on the geometrical conversion parameter.

A computing device is provided having at least one processor (104) operative to facilitate motion correction in a medical image file (102). The at least one processor (104) is configured to generate at least one unified frame file (110) based on motion image data (204), depth map data (206) corresponding to the motion image data, and region of interest data (200). Further, at least one corrected image file derived from the medical image file (102) is generated by performing the motion correction based on the at least one unified frame file (110) using the processor (104). Subsequently, the at least one corrected image file is outputted for display to one or more display devices (122).

Systems and methods for predicting images with enhanced spatial resolution using a neural network are provided herein. According to an aspect of the invention, a method includes accessing an input image of a biological sample, wherein the input image includes a first spatial resolution and a plurality of spectral images, and wherein each spectral image of the plurality of spectral images includes data from a different wavelength band at a different spectral channel; applying a trained artificial neural network to the input image; generating an output image at a second spatial resolution, wherein the second spatial resolution is higher than the first spatial resolution, and wherein the output image includes a fewer number of spectral channels than the plurality of spectral images included in the input image; and outputting the output image.

A medical image diagnostic apparatus according to an embodiment includes processing circuitry. The medical image diagnostic apparatus performs image registration between medical image data. The processing circuitry extracts a structure of the subject included in the medical image data. The processing circuitry sets a display scale of the subject to a specified value. The processing circuitry performs image registration between the medical image data on the display scale of the specified value.

The present disclosure provides a target-image acquisition method. The target-image acquisition method includes acquiring a visible-light image and an infrared (IR) image of a target, captured at a same time point by a photographing device; weighting and fusing the visible-light image and the IR image to obtain a fused image; and obtaining an image of the target according to the fused image. The present disclosure also provides a photographing device and an unmanned aerial vehicle (UAV) using the method above.

The present disclosure relates to methods and apparatuses for processing an image, training an image recognition network and recognizing an image. The method of processing an image includes: obtaining a plurality of original images from an original image set, where at least one of the plurality of original images includes an annotation area; obtaining at least one first image by splicing the plurality of original images; for each of the at least one first image, adjusting a shape and/or size of the first image based on the plurality of original images to form a second image; obtaining respective positions of the at least one annotation area in the second image by converting respective positions of the at least one annotation area in the plurality of original images.

In implementations of systems for generating candidate mirror snap points using determined axes of symmetry, a computing device implements a symmetry system to receive vector object data describing a set of points of a vector object. The symmetry system generates convex polygons that enclose the set of points and identifies a particular convex polygon that has a smallest area. A side of the particular convex polygon is determined as an axis of symmetry for the vector object. The symmetry system generates an indication for display in a user interface of a candidate snap point based on the axis of symmetry and a point of the set of points of the vector object.

The invention relates to an apparatus for generating or processing an image signal. A first image property pixel structure is a two-dimensional non-rectangular pixel structure representing a surface of a view sphere for the viewpoint. A second image property pixel structure is a two-dimensional rectangular pixel structure and is generated by a processor (305) to have a central region derived from a central region of the first image property pixel structure and at least a first corner region derived from a first border region of the first image property pixel structure. The first border region is a region proximal to one of an upper border and a lower border of the first image property pixel structure. The image signal is generated to include the second image property pixel structure and the image signal may be processed by a receiver to recover the first image property pixel structure.

A method includes aligning landmark points between multiple distorted images to generate multiple aligned images, where the multiple distorted images exhibit perspective distortion in at least one face appearing in the multiple distorted images. The method also includes predicting a depth map using a disparity estimation neural network that receives the multiple aligned images as input. The method further includes generating a warp field using a selected one of the multiple aligned images. The method also includes performing a two-dimensional (2D) image projection on the selected aligned image using the depth map and the warp field to generate an undistorted image. In addition, the method includes filling in one or more missing pixels in the undistorted image using an inpainting neural network to generate a final undistorted image.

Provided is an apparatus and method for aligning fiducial markers. The apparatus may align positions of the fiducial markers on the two or more micrographs forming a two or more point sets corresponding to the two or more micrographs; create a first set of matched fiducial markers and unmatched fiducial markers; transform unmatched fiducial markers into transformed point sets and match the unmatched fiducial markers resulting in a second set of matched fiducial markers. The matching of the second set of matched fiducial markers results in improved alignment of a large number of fiducial markers. The aligned positions of fiducial markers may be constrained by an upper bound of transformation deviation of aligning positions of fiducial markers on two or more micrographs.