The disclosure provides an appearance inspection system that can reduce subject blurring when an object is imaged while changing a relative position of an imaging device with respect to the object. A first control unit causes the imaging device to perform imaging when the imaging device reaches an imaging position corresponding to the inspection target position. A second control unit changes at least one of the position and the orientation of the imaging device in a direction in which a relative movement between a field of view of the imaging device and the inspection target position according to the change in the relative position along a designated path is canceled out during a predetermined period including a time point at which the imaging device reaches the imaging position.

This invention provides a processing apparatus for determining a state of secular change of a deformation of a construction, comprising a selection unit that selects, as a target for determination of secular change, at least a portion of deformations from among a plurality of deformations included in a first image at a first time period, on the basis of at least one of information relating to deformations, information relating to the construction, user selection, or a shape and a relative positional relationship of two or more deformations; a first determination unit that determines a deformation corresponding to a selected deformation among a plurality of deformations included in a second image at a second time period; and a second determination unit that determines a state of secular change between a selected deformation and a deformation determined by the first determination unit.

A convolutional neural network may be trained to inspect subjects such as carbon fiber propellers for surface flaws or other damage. The convolutional neural network may be trained using images of damaged and undamaged subjects. The damaged subjects may be damaged authentically during operation or artificially by manual or automated means. Additionally, images of undamaged subjects may be synthetically altered to depict damages, and such images may be used to train the convolutional neural network. Images of damaged and undamaged subjects may be captured for training or inspection purposes by an imaging system having cameras aligned substantially perpendicular to subjects and planar light sources aligned to project light upon the subjects in a manner that minimizes shadows and specular reflections. Once the classifier is trained, patches of an image of a subject may be provided to the classifier, which may predict whether such patches depict damage to the subject.

The invention relates to a non-invasive process for evaluating the quality of one or more dense connective tissue(s) in a patient, comprising the following steps: a) Analyzing the profile of the microrelief of a cutaneous replica of a portion of the skin of said patient by at least one of the following step: a1. visually assessing on picture(s) of said cutaneous replica the line shape and the anisotropy of the lines; and/or a2. Determining, on picture(s) of said cutaneous replica, the roughness index of the microrelief with an optical sensor, b) identifying cutaneous replica of stage 1, representative of healthy skins, and cutaneous replica of stage 2 representative of altered skins, a cutaneous replica of stage 2 being indicative of low quality of the one or more dense connective tissue(s) in the patients body.

There is provided a system and method of examining a specimen. The method comprises obtaining an actual measurement in response to scanning the specimen using a set of scanning parameters with predefined values; obtaining a simulated measurement based on design data; comparing the actual measurement with the simulated measurement to identify a deviation with respect to a predefined tolerance; identifying at least one structural property as root cause of the deviation by: obtaining one or more additional actual measurements in response to scanning the specimen using one or more varying values of at least one scanning parameter; and providing the actual measurement and the additional actual measurements to a simulation model representative of simulated measurement distribution in a multi-dimensional property space characterized by the structural properties of the plurality of layers and the at least one scanning parameter, thereby identifying the at least one structural property.

An information processing apparatus selects, as a reference defect, at least one defect from among first defects associated with a first image and selects, as a correction target defect, at least one defect from among second defects associated with a second image captured at a time different from an image capturing time of the first image. Additionally, the information processing apparatus generates a correction candidate by modifying the correction target defect, acquires a matching level representing a matching relationship between the reference defect and the correction candidate, and generates a corrected defect by correcting the correction target defect based on the matching level. Then, the information processing apparatus acquires a progress level representing a change in defect from the reference defect based on a comparison between the reference defect and the corrected defect.

A method of finding black spots in a separator according to an embodiment includes taking out a separator from a rechargeable battery cell; removing a foreign material of the separator surface; obtaining a first image for a portion where black spots are estimated in the separator by using a first camera and recording a position of the first image; first selecting the part where black spots are estimated by using the first image, and acquiring a second image for black spots and a foreign material other than black spots in the separator by using a second camera for the recorded position; and secondary selecting black spots by deep learning the first image and the second image with a deep learning software and then displaying the position of the black spots after.

Systems and methods for detecting defects on a wafer are provided. One method includes generating output for a wafer by scanning the wafer with an inspection system using first and second optical states of the inspection system. The first and second optical states are defined by different values for at least one optical parameter of the inspection system. The method also includes generating first image data for the wafer using the output generated using the first optical state and second image data for the wafer using the output generated using the second optical state. In addition, the method includes combining the first image data and the second image data corresponding to substantially the same locations on the wafer thereby creating additional image data for the wafer. The method further includes detecting defects on the wafer using the additional image data.

A visual inspection apparatus detects a defect candidate for each of captured images of a crown surface of a piston that are captured at a plurality of posture angles different from one another, locates a three-dimensional position of the defect candidate based on a two-dimensional position of the defect candidate detected from at least one captured image among the captured images captured at the plurality of posture angles, applies a perspective projection transformation on the three-dimensional position of the defect candidate to acquire a two-dimensional position of the defect candidate for each of the captured images captured at the plurality of posture angles, determines a feature amount regarding the defect candidate based on the two-dimensional position of the defect candidate for each of the captured images captured at the plurality of posture angles, and inspects the crown surface of the piston using the feature amount regarding the defect candidate.

A system and method for cosmetic evaluation of an electronic device, using the device's own camera or cameras to take photos of the device itself using a mirror or mirrors and using the processor of the electronic device itself to analyze its own cosmetic condition.