A method for determining an extent of anistropy of texture of an image in a manner that avoids inaccuracies arising from interpolation.

The present invention relates to a method for determining inhomogeneity in a portion of animal tissue, which provides for the arrangement beforehand of a 3-dimensional density map of said portion of tissue; the map is obtained by means of computed tomography and therefore is formed by a plurality of voxels (VX); for each voxel (VX) of the map, respectively considered as the central voxel (VXC), the following steps are carried out:—determining a space (CC) surrounding the central voxel (VXC) and containing a group of peripheral voxels (VXP),—for each peripheral voxel (VXP) of the group, calculating a value proportional to the ratio or the difference between the density of the peripheral voxel (VXP) and the density of the central voxel (VXC), thus obtaining a plurality of values,—calculating the maximum value and/or the minimum value and/or the average value and/or a statistical partitioning value of these values, thus obtaining a local indicator of inhomogeneity in the animal tissue in correspondence to the central voxel (VXC). Such method can advantageously be implemented in an equipment.

The present invention relates to a method for determining inhomogeneity in a portion of animal tissue, which provides for the arrangement beforehand of a 3-dimensional density map of said portion of tissue; the map is obtained by means of computed tomography and therefore is formed by a plurality of voxels (VX); for each voxel (VX) of the map, respectively considered as the central voxel (VXC), the following steps are carried out:—determining a space (CC) surrounding the central voxel (VXC) and containing a group of peripheral voxels (VXP),—for each peripheral voxel (VXP) of the group, calculating a value proportional to the ratio or the difference between the density of the peripheral voxel (VXP) and the density of the central voxel (VXC), thus obtaining a plurality of values,—calculating the maximum value and/or the minimum value and/or the average value and/or a statistical partitioning value of these values, thus obtaining a local indicator of inhomogeneity in the animal tissue in correspondence to the central voxel (VXC). Such method can advantageously be implemented in an equipment.

A method for detecting a defect on a surface of a tire includes automated steps of: calculating values of a gradient of a plurality of texture parameters from an image of the surface of the tire, determining an image of the gradient, and thresholding of the image of the gradient to obtain a thresholded image.

A method for detecting a defect on a surface of a tire includes automated steps of: calculating values of a gradient of a plurality of texture parameters from an image of the surface of the tire, determining an image of the gradient, and thresholding of the image of the gradient to obtain a thresholded image.

In one embodiment, the disclosure relates to a method for determining a degree of homogeneity in one or more inspection images of cargo in one or more containers, comprising: determining whether a zone of interest in one or more processed inspection images comprises one or more patterns, wherein the one or more processed inspection images are processed from one or more inspection images generated by an inspection system configured to inspect the one or more containers; and in the event that one or more patterns is determined and that a variation in the determined one or more patterns is identified, classifying the one or more inspection images as having a degree of homogeneity below a predetermined homogeneity threshold.

A system and method for determining coating requirements with one or more computer-based systems, which includes receiving image files of a structure (e.g., a building), identifying one or more surfaces of the structure to be coated based on the received image files, determining a surface area for each of one or more surfaces to be coated, receiving coating application information, calculating a coating amount for each of the one or more surfaces to be coated based on the calculated surface area and the received coating application information, and optionally, communicating the calculated coating amounts.

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.

A system and method is provided for automated polyp detection in optical colonoscopy images. The system includes an input configured to acquire a series of optical images, and a processor configured to process the optical images. Processing steps include performing a boundary classification with steps comprising locating a series of edge pixels using at least one acquired optical image, selecting an image patch around each said edge pixel, performing a classification threshold analysis on each image patch of said edge pixels using a set of determined boundary classifiers, and identifying, based on the classification threshold analysis, polyp edge pixels consistent with a polyp edge. Processing steps for the processor also include performing a vote accumulation, using the identified polyp edge pixels, to determine a polyp location. The system also includes an output configured to indicate potential polyps using the determined polyp location.

A system and method is provided for automated polyp detection in optical colonoscopy images. The system includes an input configured to acquire a series of optical images, and a processor configured to process the optical images. Processing steps include performing a boundary classification with steps comprising locating a series of edge pixels using at least one acquired optical image, selecting an image patch around each said edge pixel, performing a classification threshold analysis on each image patch of said edge pixels using a set of determined boundary classifiers, and identifying, based on the classification threshold analysis, polyp edge pixels consistent with a polyp edge. Processing steps for the processor also include performing a vote accumulation, using the identified polyp edge pixels, to determine a polyp location. The system also includes an output configured to indicate potential polyps using the determined polyp location.