In a data processing system, an input data array to be downscaled is split into plural parts along its horizontal extent and the different parts of the input data array are then provided to respective scalers of the data processing system and are respectively downscaled by those scalers to provide a plurality of downscaled output parts. The plural downscaled output parts are then combined (merged) to provide the desired downscaled output data array.

A device includes a memory configured to store instructions and a processor configured to execute the instructions to obtain image data of a region of interest included in an image frame. The processor may also be configured to compare the image data of the region of interest with image data of a background to detect a change in the region of interest. The processor may further be configured to detect the object in image frame based on the detected change.

Disclosed is a distortion rectification method, comprising: taking a wide-angle photograph using a camera of a terminal; determining distortion regions and non-distortion regions in the wide-angle photograph; obtaining a target distortion region selected by a user; dividing the target distortion region into M grid regions of a first pre-set size, wherein M is an integer greater than or equal to one; and respectively performing distortion rectification on the M grid regions of the first pre-set size. Also disclosed is a terminal.

An object having a high attention degree is selected from objects detected by a detection means, brightness of a captured image is calculated by using an attention region corresponding to the selected object as a detection frame, and exposure control is performed based on the calculated brightness. The attention degree is evaluated higher with the decrease in the distance. Alternatively, the attention degree is evaluated higher as the direction becomes closer to the traveling direction. The attention region is made larger with the decrease in the distance to the object. It is also possible to judge the type of the object and determine the size of the attention region based on the result of the judgment. A subject to be paid attention to is made clearly visible.

In an apparatus, it is determined whether a covariance matrix calculated based on a plurality of patches is abnormal. In a case where it is determined that the covariance matrix is not abnormal, the covariance matrix is used to perform first correction on pixels included in the plurality of patches. In a case where it is determined that the covariance matrix is abnormal, second correction, which is different from the first correction, is performed on the pixels included in the plurality of patches.

An image evaluation device includes a determination result acquisition unit acquires a result of determining the presence or absence of a difference between an object image that is one of a plurality of images that include three or more images obtained by imaging substantially the same spatial region and each of reference images that are images other than the object image among the plurality of images and an evaluation index acquisition unit configured to acquire an evaluation index for the plurality of images on the basis of at least one of the number of determinations of the presence of the difference between the object image and each reference image and the number of determinations of the absence of the difference between the object image and each reference image.

A method of generating a 3D reconstruction of a scene, the scene comprising a plurality of cameras positioned around the scene, comprises: obtaining the extrinsics and intrinsics of a virtual camera within a scene; accessing a data structure so as to determine a camera pair that is to be used in reconstructing the scene from the viewpoint of the virtual camera; wherein the data structure defines a voxel representation of the scene, the voxel representation comprising a plurality of voxels, at least some of the voxel surfaces being associated with respective camera pair identifiers; wherein each camera pair identifier associated with a respective voxel surface corresponds to a camera pair that has been identified as being suitable for obtaining depth data for the part of the scene within that voxel and for which the averaged pose of the camera pair is oriented towards the voxel surface; identifying, based on the obtained extrinsics and intrinsics of the virtual camera, at least one voxel that is within the field of view of the virtual camera and a corresponding voxel surface that is oriented towards the virtual camera; identifying, based on the accessed data structure, at least one camera pair that is suitable for reconstructing the scene from the viewpoint of the virtual camera, and generating a reconstruction of the scene from the viewpoint of the virtual camera based on the images captured by the cameras in the identified at least one camera pair.

Disclosed is an image quality evaluation method for a digital pathology system according to the present invention. The image quality evaluation method includes receiving a digital slide image by an image quality evaluation unit; dividing the digital slide image into a plurality of blocks by the image quality evaluation unit; analyzing the plurality of blocks to extract a foreground; calculating a blur for the extracted foreground; calculating brightness distortion for the extracted foreground; calculating contrast distortion for the extracted foreground; and evaluating the overall quality of the digital slide image using the blur, the brightness distortion, and the contrast distortion by the image quality evaluation unit.

In one embodiment, an apparatus comprises a memory and a processor. The memory is to store visual data associated with a visual representation captured by one or more sensors. The processor is to: obtain the visual data associated with the visual representation captured by the one or more sensors, wherein the visual data comprises uncompressed visual data or compressed visual data; process the visual data using a convolutional neural network (CNN), wherein the CNN comprises a plurality of layers, wherein the plurality of layers comprises a plurality of filters, and wherein the plurality of filters comprises one or more pixel-domain filters to perform processing associated with uncompressed data and one or more compressed-domain filters to perform processing associated with compressed data; and classify the visual data based on an output of the CNN.

A method for controlling a near field communication between a device and a transaction card is disclosed. The method includes the steps of capturing, by a front-facing camera of the device, a series of images of the transaction card and processing each image of the series of images to identify a darkness level associated with a distance of the transaction card from the front of the device. The method includes comparing each identified darkness level to a predetermined darkness level associated with a preferred distance for a near field communication read operation and automatically triggering a near field communication read operation between the device and the transaction card for the communication of a cryptogram from an applet of the transaction card to the device in response to the identified darkness level corresponding to the predetermined darkness level associated with the preferred distance for the near field communication read operation.