An information processing apparatus for determining an area of a packaged object in a packaging material to suctioned by a suction device for picking up the packaged object includes an input unit configured to input an image obtained by capturing the packaged object, and a determining unit configured to, based on a state of a surface of the packaging material regarding a degree of ease of suction in each area of the surface of the packaging material identified based on the image, determine the area to be suctioned by the suction device.

An information processing apparatus for determining an area of a packaged object in a packaging material to suctioned by a suction device for picking up the packaged object includes an input unit configured to input an image obtained by capturing the packaged object, and a determining unit configured to, based on a state of a surface of the packaging material regarding a degree of ease of suction in each area of the surface of the packaging material identified based on the image, determine the area to be suctioned by the suction device.

Apparatus and methods for image processing are provided. Imaging devices may be coupled to movable objects, such as unmanned aerial vehicles (UAVs). One or more images may be captured by an imaging device, such as a camera. The one or more images may be captured under the same or different parameters. The one or more captured images may be processed for use in computer vision applications. Processing the one or more captured images may involve analyzing a texture of the images. Subsequent images may be captured under the same or different parameters.

Apparatus and methods for image processing are provided. Imaging devices may be coupled to movable objects, such as unmanned aerial vehicles (UAVs). One or more images may be captured by an imaging device, such as a camera. The one or more images may be captured under the same or different parameters. The one or more captured images may be processed for use in computer vision applications. Processing the one or more captured images may involve analyzing a texture of the images. Subsequent images may be captured under the same or different parameters.

In one embodiment, a method includes receiving measured linescan information describing a pattern structure of a feature, applying the received measured linescan information to an inverse linescan model that relates measured linescan information to feature geometry information, and identifying, based at least in part on the applying the received measured linescan model to the inverse linescan model, feature geometry information that describes a feature that would produce a linescan corresponding to the received measured linescan information. The method also includes determining, at least in part using the inverse linescan model, feature edge positions of the identified feature, analyzing the feature edge positions to determine errors in the manufacture of the pattern structure, and controlling a lithography tool based on the analysis of the feature edge positions.

In one embodiment, a method includes receiving measured linescan information describing a pattern structure of a feature, applying the received measured linescan information to an inverse linescan model that relates measured linescan information to feature geometry information, and identifying, based at least in part on the applying the received measured linescan model to the inverse linescan model, feature geometry information that describes a feature that would produce a linescan corresponding to the received measured linescan information. The method also includes determining, at least in part using the inverse linescan model, feature edge positions of the identified feature, analyzing the feature edge positions to determine errors in the manufacture of the pattern structure, and controlling a lithography tool based on the analysis of the feature edge positions.

A method for calculating a coating textures indicator can comprise receiving target coating texture variables from an image. The method can also comprise accessing a relative texture characteristic database that stores a set of texture characteristic relationships for a plurality of coatings. The method can further comprise calculating a correlation between the target coating texture variables and target coating texture variables associated with a compared coating. Based upon the calculated correlation, the method can comprise, calculating a set of relative texture characteristics for the target coating that indicate relative differences in texture between the target coating and the compared coating. Each of the relative texture characteristics can comprise an assessment over all angles of the target coating.

An individual identification apparatus that identifies an individual product having a pattern of irregularities randomly formed on a surface thereof includes an imaging unit and an extracting unit. The imaging unit is configured to acquire an image obtained by capturing a date mark formed on the product. The extracting unit is configured to extract a feature value related to the pattern of the irregularities from the image as data identifying the individual product.

An individual identification apparatus that identifies an individual product having a pattern of irregularities randomly formed on a surface thereof includes an imaging unit and an extracting unit. The imaging unit is configured to acquire an image obtained by capturing a date mark formed on the product. The extracting unit is configured to extract a feature value related to the pattern of the irregularities from the image as data identifying the individual product.

A method is disclosed. The method includes receiving measured linescan information describing a pattern structure of a feature, applying the received measured linescan information to an inverse linescan model that relates measured linescan information to feature geometry information, identifying, based at least in part on the applying the received measured linescan model to the inverse linescan model, feature geometry information that describes a feature that would produce a linescan corresponding to the received measured linescan information, determining, at least in part using the inverse linescan model, feature edge positions of the identified feature, and analyzing the feature edge positions to detect the presence or absence of defects in the pattern structure.