A camera mounted on a seafaring vessel obtains an image showing an object. The distance to the object is computed using, in part, a normal vector of the plane containing the camera and the horizon.

A camera mounted on a seafaring vessel obtains an image showing an object. The distance to the object is computed using, in part, a normal vector of the plane containing the camera and the horizon.

A measurement section (1) performs a mass spectrometric analysis for each micro area within a measurement area on a sample. A dimension reduction processor (23) performs data processing by non-linear dimension reduction using manifold learning on mass spectrometric data for each micro area, to obtain, for each micro area, a set of data reduced to three dimensions from the dimensions corresponding to the number of mass-to-charge-ratio values. A display color determiner (24) determines a color for each of the points corresponding to the data of the micro areas after the dimension reduction, by arranging those points within a three-dimensional space having three axes representing the three dimensions, with three primary colors respectively assigned to the three axes. A segmentation image creator (25) creates a segmentation image corresponding to the measurement area or a partial area in the measurement area, by arranging, on two dimensions, pixels which respectively correspond to the points within the three-dimensional space, where each pixel has a color given to the point corresponding to the pixel and is located according to the position within the measurement area of the micro area corresponding to the point.

Presented are concepts for adapting a first, pre-defined mesh topology representing an organ to a second, different mesh topology of the organ. One such concept includes identifying correspondence between the first and second mesh topologies based on spectral matching of the first and second mesh topologies. The first, predefined mesh topology is aligned with the second mesh topology based on the identified correspondence between the first and second mesh topologies.

A method and a system for measuring intra-site heterogeneity in a tumor using magnetic resonance imaging (MRI). The method includes acquiring magnetic resonance (MR) images using MRI modality; segmenting tumor sites in the MR images; dividing each of the tumor sites into a plurality of sub-regions; deriving image biomarkers from each voxel or pixel in the plurality of sub-regions; classifying each voxel or pixel in the plurality of sub-regions into genotypes or molecular subtypes based on the extracted image biomarkers and a classifier model including associations between image biomarkers and genotypes or molecule subtypes; creating a distribution of genotypes or molecular subtypes in the each of the plurality of sub-regions based on classifications of voxels or pixels; generating spatial information of genotypes or molecular subtypes in the tumor sites based on the distribution; and measuring intra-site heterogeneity in the tumor sites.

A method and a system for measuring intra-site heterogeneity in a tumor using magnetic resonance imaging (MRI). The method includes acquiring magnetic resonance (MR) images using MRI modality; segmenting tumor sites in the MR images; dividing each of the tumor sites into a plurality of sub-regions; deriving image biomarkers from each voxel or pixel in the plurality of sub-regions; classifying each voxel or pixel in the plurality of sub-regions into genotypes or molecular subtypes based on the extracted image biomarkers and a classifier model including associations between image biomarkers and genotypes or molecule subtypes; creating a distribution of genotypes or molecular subtypes in the each of the plurality of sub-regions based on classifications of voxels or pixels; generating spatial information of genotypes or molecular subtypes in the tumor sites based on the distribution; and measuring intra-site heterogeneity in the tumor sites.

An object detection device includes a processor. The processor is configured to apply a Hough transform to coordinate points on a UD map to detect a straight line having a predetermined length, and detect a target disparity corresponding to the detected straight line having the predetermined length as a disparity corresponding to an object parallel to a direction of travel of a stereo camera. In the UD map, a target disparity satisfying a predetermined condition among disparities acquired from a captured image is associated with coordinate points, each of the coordinate points having two-dimensional coordinates formed by a first direction and a direction corresponding to a magnitude of a disparity. The processor is configured to convert, in the Hough transform, a straight line passing through coordinate points associated with the target disparity and a predetermined range based on a vanishing point into a Hough space.

An object detection device includes a processor. The processor is configured to apply a Hough transform to coordinate points on a UD map to detect a straight line having a predetermined length, and detect a target disparity corresponding to the detected straight line having the predetermined length as a disparity corresponding to an object parallel to a direction of travel of a stereo camera. In the UD map, a target disparity satisfying a predetermined condition among disparities acquired from a captured image is associated with coordinate points, each of the coordinate points having two-dimensional coordinates formed by a first direction and a direction corresponding to a magnitude of a disparity. The processor is configured to convert, in the Hough transform, a straight line passing through coordinate points associated with the target disparity and a predetermined range based on a vanishing point into a Hough space.

A method of barrier detection in an imaging controller includes: obtaining an image of a support structure configured to support a plurality of items on a support surface extending between a shelf edge and a shelf back; extracting frequency components representing pixels of the image; based on the extracted frequency components, identifying a barrier region of the image, the barrier region containing a barrier adjacent to the shelf edge; and detecting at least one empty sub-region within the barrier region, wherein the empty sub-region is free of items between the barrier and the shelf back.

A method of barrier detection in an imaging controller includes: obtaining an image of a support structure configured to support a plurality of items on a support surface extending between a shelf edge and a shelf back; extracting frequency components representing pixels of the image; based on the extracted frequency components, identifying a barrier region of the image, the barrier region containing a barrier adjacent to the shelf edge; and detecting at least one empty sub-region within the barrier region, wherein the empty sub-region is free of items between the barrier and the shelf back.