The present disclosure discloses user equipment and an image processing method and apparatus, which relate to the field of information technologies and can improve accuracy in determining image depth information. The method includes: first obtaining an original image, then determining, according to the original image and at least two preset edge image blocks, a target blur value corresponding to a pixel in the original image, and finally, determining a depth value corresponding to the pixel in the original image according to the target blur value corresponding to the pixel in the original image. The present invention is applicable to determining of a blur value corresponding to a pixel in an image and determining of a depth value corresponding to the pixel in the image according to the blur value corresponding to the pixel in the image.

An image processing system includes: an analysis unit configured to obtain information indicating a degree of curvature of a retina from a tomographic image of an eye to be examined; and an obtaining unit configured to obtain a category of the eye to be examined based on an analysis result.

An image processing system includes: an analysis unit configured to obtain information indicating a degree of curvature of a retina from a tomographic image of an eye to be examined; and an obtaining unit configured to obtain a category of the eye to be examined based on an analysis result.

Various examples are provided related to determination of contact angle of sessile drops. In one example, a method includes determining a volume of a sessile drop of fluid disposed on a test surface; determining a height of the sessile drop of fluid; and determining a contact angle of the sessile drop of fluid based upon the volume and the height of the sessile drop. In another example, a system includes a volume sensing, a height sensing, and computing that can determine a volume and height of a sessile drop using volume and height data from the sensing, and determine a contact angle of the sessile drop with the volume and the height. The contact angle and surface tension can be determined with at least three of volume, a height, a footprint radius, a radius of maximum horizontal extent, and/or an apex radius of curvature of the drop.

A method for contact-free axle counting of a vehicle on a road, including a step of reading in first image data and reading in second image data, wherein the first image data and/or the second image data represent image data provided to an interface by an image data recording sensor arranged on a side of the road. The first image data and/or the second image data comprise an image of the vehicle. The first image data and/or the second image data is processed in order to obtain processed first image data and/or processed second image data. By using the first image data and/or the second image data in a substep of detecting, at least one object is detected in the first image data and/or the second image data, and wherein object information is provided representing the object and assigned to the first image data and/or the second image data.

A dynamic analysis apparatus, including a processor which selects one or more frame images from a plurality of frame images of a dynamic image that is obtained by performing radiation imaging of a subject including a target site in a living body, recognizes a shape of a predetermined body part from each of the selected one or more frame images and calculates an evaluation value of the recognized shape of the body part.

A book detection apparatus detects a plurality of surface regions on the basis of three-dimensional measurement data that is obtained by a three-dimensional sensor and that falls within a search area, and determines, when a positional relationship between two surface regions among the plurality of surface regions satisfies a positional condition corresponding to a positional relationship between two opened pages of an opened book, the two surface regions as a book region that includes the book.

A book detection apparatus detects a plurality of surface regions on the basis of three-dimensional measurement data that is obtained by a three-dimensional sensor and that falls within a search area, and determines, when a positional relationship between two surface regions among the plurality of surface regions satisfies a positional condition corresponding to a positional relationship between two opened pages of an opened book, the two surface regions as a book region that includes the book.

There provides an apparatus for recognizing a head region in a CT lateral image of a subject, comprising: a deriving unit for deriving a first image representing a bone of the subject from the CT lateral image; an extracting unit for extracting a boundary curve indicating an outer contour of a region comprising at least part of the occipital bone and at least part of the cervical vertebra of the subject in the first image; and a determining unit for determining a first pixel position indicating a bottommost point of the head region of the subject, based on a shape feature parameter of the boundary curve.

Described is a computer-implemented method for determining uncertainties in measurement data from a measurement of an object, wherein a digital representation of the object is generated by the measurement. The object representation has items of image information, which each indicate a value of a measurement variable for the object at a defined position of the object. Statistical noise is superimposed on the image information. The method includes determining the object representation, determining a distance field from the image information relating to the object representation, determining a strength of the statistical noise in the image information, determining an uncertainty of the distance values of the distance field on the basis of the strength of the statistical noise, and determining an uncertainty of the position of at least one point on at least one material boundary surface from the uncertainty of the distance values of the distance field.