A shape measurement system includes one or more lighting units located in a case that illuminate a target object located in the case, one or more image capture units located in the case that capture an image of the target object, a holding unit that holds the image capture units and the lighting units so as to form a polyhedron shape approximating a sphere, a selector that selects at least one of the image capture units and at least one of the lighting units to be operated, and a shape calculator that calculates a 3-D shape of the target object based on image data captured by the selected image capture unit under light emitted by the selected lighting unit.

A device may use a camera to capture an image of an end face of an optical fiber in a field of view of the camera. The device may monitor a focus metric associated with the image while the image is manually focused using an opto-mechanical assembly. The device may automatically initiate a test to inspect the image of the end face of the optical fiber for compliance with a set of criteria related to cleanliness and damage based on the focus metric satisfying a condition. The device may output a result from the test indicating whether the end face of the optical fiber satisfies the set of criteria related to cleanliness and damage.

Methods and apparatus for generating a sharp image are described. A camera device includes a plurality of camera modules, e.g., optical chains, where at least some of the camera modules have different depths of field. Multiple images of a scene are captured using the plurality of camera modules. Portions of the multiple images which correspond to the same scene area are identified. Image portion sharpness levels are determined for individual image portions. Image portions with high sharpness levels are selected and included in a composite image.

The image capturing control apparatus to control an image capturing apparatus that performs still image capturing of a moving object with drive of a movable element movable in a direction other than an optical axis direction of an image capturing optical system. The control apparatus includes a vector acquisition unit to acquire multiple motion vectors respectively detected in multiple object areas of a captured moving image produced by the image capturing apparatus, and a control unit to control the still image capturing with a drive control of the movable element. The control unit causes the image capturing apparatus, when the multiple motion vectors have mutually different magnitudes, to perform the still image capturing multiple times with the drive controls of the movable element while changing a drive amount of the movable element on the basis of the respective multiple motion vectors.

Methods and systems for determining information for a specimen are provided. Certain embodiments relate to bump height 3D inspection and metrology using deep learning artificial intelligence. For example, one embodiment includes a deep learning (DL) model configured for predicting height of one or more 3D structures formed on a specimen based on one or more images of the specimen generated by an imaging subsystem. One or more computer systems are configured for determining information for the specimen based on the predicted height. Determining the information may include, for example, determining if any of the 3D structures are defective based on the predicted height. In another example, the information determined for the specimen may include an average height metric for the one or more 3D structures.

A method is disclosed for ascertaining a focus image distance of an optical sensor, which is provided with a lens, of a coordinate-measuring apparatus onto a workpiece to be measured, wherein the optical sensor and/or the workpiece are movable in a Z direction such that a distance in the Z direction between the workpiece and the optical sensor is variable. Further, a corresponding coordinate-measuring apparatus and a computer program product are disclosed.

Disclosed herein is a system to smoothly change the focus of a camera between multiple targets. The system can obtain an indication of a target, an indication of a manner of focus transition between a first target and a second target, and camera settings. The system can determine a point associated with the second target, where the point has a property that focusing the camera on the point places the second target in focus, and the point is closer to the current focus point of the camera than a substantial portion of other points having the property. The system can obtain a nonlinear function indicating a second manner of focus transition between the first target and the second target. The system can change the focus of the camera between the first target and the second target by changing the focus of the camera from the current focus point to the determined point based on the nonlinear function.

A method is provided for determining the distance between two optical boundary surfaces spaced apart from each other in a first direction. A first image is ascertained wherein the plane into which the pattern acquired coincides with a first of two optical boundary surfaces or has the smallest distance to the first optical boundary surface in a first direction. A position of the first image in the first direction is determined. A second image is ascertained wherein the plane into which the pattern acquired coincides with a second of two optical boundary surfaces or has the smallest distance to the second optical boundary surface in the first direction. The position of the second image in the first direction is determined. The distance is calculated by means of determined positions of the first and second image.

Methods, systems, and computer-readable media for processing spatially related sequence data received from a sequencing device are presented. In one or more embodiments, a computing platform may receive, from a sequencing device, image data associated with a sample. The computing platform may identify, based on the image data received from the sequencing device, a first sequence located at first spatial coordinates. Subsequently, the computing platform may store, in a spatially searchable database, a first data element comprising the first spatial coordinates and a first identifier corresponding to the first sequence to spatially relate the first sequence to other sequences present in the sample. In some instances, the image data received from the sequencing device may include spatial information, temporal information, and color information associated with the sample, and the computing platform may present, on a display device, information identifying a presence of the first sequence at the first spatial coordinates.

A cell observation apparatus includes an imaging device capable of imaging a vessel containing cells while varying a focal position, an illuminating device for irradiating the vessel with illuminating light; and a controller for controlling the imaging device. The controller includes: a z-stack imaging controller for causing the imaging device to take a plurality of z-stack images while varying the focal position; a variance value calculation part for calculating a variance value of pixels values for each of the z-stack images; an edge index value calculation part for calculating an edge index value indicative of edge strength for each of the z-stack images; a focus evaluation value calculation part for calculating a focus evaluation value having a minimum value in an in-focus position, based on the variance value and the edge index value; and an in-focus position estimation part for calculating the focal position where the focus evaluation value has a minimum value to estimate the in-focus position. This achieves the estimation of the in-focus position with high precision while suppressing the increase in the number of images taken for z-stack imaging.