Provided is the technique that allows an operator or the like to easily grasp a defect contained in a mold. A display control device is configured to carry out: a determination process in which a feature amount of each of defects contained in a mold is determined with reference to an image obtained by image capture of a mold; and a display process in which the image is displayed on a display such that each of the defects in the image is emphasized by a method which is determined according to the determined feature amount.

Provided is a technique that allows an operator or the like to easily perceive a tendency of defects which are present in molds or patterns. A display device displays a result of inspection of a plurality of molds or a plurality of patterns which are inspection target objects. The display device classifies the inspection target objects into a plurality of groups, generates, for each of the plurality of groups, a heat map image from a result of defect inspection of one or more of inspection target objects which are classified into the each of the plurality of groups, the heat map image representing a spatial distribution of defect occurrence frequencies; and causes a display to display one or more of the heat map images generated, the one or more heat map images corresponding to one or more groups specified by a user from among the plurality of groups.

The present specification provides a film defect detection system. The film defect detection system may comprise an image acquisition unit configured to acquire an image of a film in a manufacturing process of the film; a defect detection unit configured to detect defects in the film by analyzing the acquired image of the film, using a machine learning algorithm learned to detect a defect in advance, when receiving the acquired image of the film; and an information output unit configured to output information on the defects in the film detected by the defect detection unit.

A method and system provide the ability to examine a three-dimensional (3D) structure. A physical 3D structure is acquired. A digital model of the 3D structure is acquired in an augmented reality (AR) system. The digital model is calibrated to match the 3D structure. The digital model is projected onto the 3D structure. A tool interacting with the 3D structure is tracked and the interaction is analyzed. A visualization of the projected digital model is updated based on the analysis.

A method for the non-destructive testing of the volume of a test object, during the course of which a volume raw image of the test object is recorded by a suitable non-destructive imaging testing method. Then, those regions of the volume raw image are identified that are not to be attributed to the test object material. It is checked whether an identified region is completely embedded in regions that are to be associated with the test object material. If necessary, such a region is assimilated to those regions that are to be associated with the test object material, forming a filled volume raw image. Finally, a difference is generated between the volume raw image and the filled volume raw image, forming a first flaw image.

A controller measures a three-dimensional surface shape of a workpiece from an image of the workpiece, the image being taken by an imaging unit and the image including a specific optical pattern projected by the imaging unit. The controller collates the measured three-dimensional surface shape of the workpiece and a nominal contour data representing a three-dimensional surface shape of a non-defective product corresponding to the workpiece, and the controller detects, as a possible molding fault, a portion recognized to show a shape different from the three-dimensional surface shape of the non-defective product in the workpiece. The controller specifies, as a molding fault, among the detected possible molding faults, only a possible molding fault in which a dimension of the shape is equal to or more than a criterion value representing a criterion for the molding fault.

Described is a method for segmenting measurement data from measurement of an object that has at least one material transition region. The measurement data are used to generate a digital object representation that has the material transition region and a multiplicity of spatially resolved image information items relating to the object. The method may include: determining measurement data that have at least one small structure having an extent which is less than a predefined extent; determining at least two homogeneous regions in the measurement data and/or in the digital object representation, wherein at least one homogeneous regions has a small structure; analysing a local similarity of the multiplicity of spatially resolved image information items; adapting an extent of each homogeneous region until at least one border region is arranged at an expected position of a material transition region; and segmenting the digital object representation based on the adapted homogeneous regions.

A method for quantitatively measuring internal defects in an as-cast steel product includes optically scanning at least a portion of a surface of the steel product with a scanning device to create a digital image thereof, analyzing the digital image to calculate a quantitative value for an amount of internal defects therein, and normalizing the quantitative value to a rating according to a standardized scale.

A spatial difference measurement method, can include generating first key features of a first skeleton of a nominal 3D model of an object and extrapolating the first key features onto the nominal 3D model. The method can include creating an actual 3D model of the object during or after a construction process (real or simulated). The method can include generating second key features of a second skeleton of the actual 3D model of the object and extrapolating the second key features onto the actual 3D model of the object. The method can include comparing the first key features extrapolated on the nominal 3D model to the second key features extrapolated on the actual 3D model to determine one or more distances between the first and second key features to measure a spatial difference between the nominal 3D model and the object during or after construction.

An appearance determination device includes at least one processor. The at least one processor carries out a determination step of determining whether an object of determination is conforming or nonconforming, in accordance with a color image and a shape image, the color image being generated by photometric stereo and representing a color optical image of the object of determination, the shape image being generated by the photometric stereo and representing a shape of the object of determination.