Provided are an image processing device and the like which implement personal privacy protection while suppressing a reduction in visibility for an image. The image processing device is provided with: a memory storing instructions; and one or more processors configured to execute the instructions to: detect a person region that is a region where a person appears in an image captured by a camera device; and perform, on the person region, privacy processing a strength of which differs according to a depth associated with coordinates of the person region or a predetermined index related to the depth.

Provided are an image processing device and the like which implement personal privacy protection while suppressing a reduction in visibility for an image. The image processing device is provided with: a memory storing instructions; and one or more processors configured to execute the instructions to: detect a person region that is a region where a person appears in an image captured by a camera device; and perform, on the person region, privacy processing a strength of which differs according to a depth associated with coordinates of the person region or a predetermined index related to the depth.

A method, apparatus and computer program product for removing weather elements, such as rain, from images are provided. In this regard, imagery from self-driving cars or video surveillance may be blurred by weather elements. The weather elements may be removed by utilizing pure weather element images. The pure weather element images may be processed by machine learning techniques to model pure weather element data, and generate a pure weather element dictionary. Imagery including both weather elements and background scenery may then be processed accordingly, and the weather elements removed based on the learned pure weather element dictionary. Resulting weather-free images may then be generated.

Embodiments include methods, systems, and computer program products for remediating a color vision deficiency. Aspects include receiving a time dependent location information for a user. Aspects also include receiving images of a plurality of objects, wherein each of the plurality of objects corresponds to the time dependent location information and, for each of the plurality of objects, identifying an object type and an object color. Aspects also include determining a number of distinguishable colors required to remediate a color vision deficiency and a number of available colors and overlaying one of the plurality of objects with an available color responsive to a determination that the number of distinguishable colors does not exceed the number of available colors.

An image acquisition unit acquires a plurality of medical images, and a common region determination unit determines common regions commonly present in the plurality of medical images. An enlargement ratio determination unit determines an enlargement ratio, which is for displaying the plurality of common regions in the plurality of medical images with the same size, for each of the plurality of medical images. A display control unit applies the determined enlargement ratio to the plurality of common regions, and displays images of the plurality of common regions after applying the enlargement ratio on a display.

A computer-based, automated grading system us configured to receive human-generated source code in a machine-readable format to score the quality of the subject code against a target design specification. An assessment web application administers an assessment and receives a candidate submission that may be injected into a reference codebase, rendered in a browser, and processed by a mismatch generator and scorer to calculate a candidate submission score.

An image processing method. The method includes: An electronic device obtains N images, where the N images have a same quantity of pixels and a same pixel location arrangement, and N is an integer greater than 1; the electronic device obtains, based on feature values of pixels located at a same location in the N images, a reference value of the corresponding location; the electronic device determines a target pixel of each location based on a reference value of the location; and the electronic device generates a target image based on the target pixel of each location.

At least one processor of an image processing system acquires a target object image including a target object. The at least one processor executes matching for the target object image based on a template image including a feature about the target object. The at least one processor analyzes a plurality of scores acquired through the matching. The at least one processor determines, based on a result of analysis of the plurality of scores, whether the target object in the target object image is blurred.

In exemplary embodiments, methods and systems are provided that include or utilize one or more automotive equipped cameras and a processor. The one or more automotive equipped cameras are configured to be onboard a vehicle and to obtain camera images during operation of the vehicle, the camera images including a view of one or more wheels of the vehicle. The processor is coupled to the one or more cameras, and is configured to at least facilitate: processing the camera images; and determining one or more states of the one or more wheels, including an alignment thereof, a health thereof, or both, based on the processing of the camera images.

A method is disclosed that includes receiving, by a processing device, a plurality of images of a test assembly. The processing device selects a component in the test assembly and an image of the plurality of images of the test assembly as received. For the component as selected and the image as selected, the processing device compares a plurality of portions of the image as selected to a corresponding plurality of portions of a corresponding profile image and computing a matching score for each of the plurality of portions. The processing device selects a largest matching score from the matching score for each of the plurality of portions as a first matching score for the component as selected and the image as selected. The first matching score is stored for the component as selected and the image as selected.