An acquired image is analysed to determine a test outcome value. A shape template for a test structure is provided to identify a position of a target measurement region on the test structure. A mapping defining a transformation of the shape template onto the image frame is determined. A mapping is determined and it is determined if a first matching condition based on first displacements of one or more edges identified in the image frame relative to the shape template is satisfied for the mapping. When the mapping satisfies the first matching condition and a second different matching condition based on second displacements of one or more edges identified in the image frame relative to the shape template, a verified image of a test structure is established. In the verified image of the test structure a target measurement region is identified. A test outcome value is determined by analysing the target measurement region.

Systems and methods for automatically excluding artifacts from an analysis of a biological specimen image are disclosed. An exemplary method includes obtaining an immunohistochemistry (IHC) image and a control image, determining whether the control image includes one or more artifacts, upon a determination that the control image includes one or more artifacts, identifying one or more artifact regions within the IHC image by mapping the one or more artifacts from the control image to the IHC image, and performing image analysis of the IHC image where any identified artifact regions are excluded from the image analysis.

Example image processing methods, apparatus/systems and articles of manufacture are disclosed herein. An example apparatus includes an image recognition application to identify matches between stored patterns and objects detected in a shelf image, where the shelf image has a shelf image scale estimate. The example apparatus further includes a scale corrector to calculate deviation values between sizes of (A) a first set of the objects detected in the shelf image and (B) a first set of the stored patterns matched with the first set of the objects and reduce an error of the shelf image scale estimate by calculating a scale correction value for the shelf image scale estimate based on the deviation values.

Embodiments of the present disclosure disclose image processing methods and apparatuses, image devices, and storage media. The image processing method includes: obtaining an image; obtaining the feature of the limb of the body based on the image, where the limb includes the upper limb and/or the lower limb; determining first-type movement information of the limb based on the feature; and controlling the movement of the limb of a controlled model according to the first-type movement information.

Embodiments of the present disclosure disclose an image processing method and apparatus, an image device, and a storage medium. The image processing method includes: obtaining an image; obtaining a feature of a part of a target based on the image; determining movement information of the part based on the feature; and controlling movement of a corresponding part in a controlled model according to the movement information.

Embodiments of the present disclosure disclose an image processing method and apparatus, an image device, and a storage medium. The image processing method includes: obtaining an image; obtaining features of at least two parts of a target based on the image; determining, according to the features of the at least two parts and a first movement constraint condition of a connection portion, movement information of the connection portion, where the connection portion connects two of the at least two parts; and controlling the movement of the connection portion in a controlled model according to the movement information of the connection portion.

Embodiments of the present disclosure disclose an image processing method and apparatus, an image device, and a storage medium. The image processing method includes: obtaining an image; obtaining first rotation information of each of multiple nodes of a target; determining second rotation information of each child node with respect to a parent node in the multiple nodes of the target according to a hierarchical relationship among the nodes and multiple pieces of the first rotation information; and controlling movements of nodes in a controlled model corresponding to the multiple nodes based on multiple pieces of the second rotation information.

An example system includes a stand configured to position a computing device proximate to a physical activity surface. The system further includes a video capture device, a detector, and an activity application. The video capture device is coupled for communication with the computing device and is adapted to capture a video stream that includes an activity scene of the physical activity surface and one or more interface objects physically interactable with by a user. The detector is executable to detect motion in the activity scene based on the processing and, responsive to detecting the motion, process the video stream to detect one or more interface objects included in the activity scene of the physical activity surface. The activity application is executable to present virtual information on a display of the computing device based on the one or more detected interface objects.

The present application provides a comparison method and a modeling method for a chip product, a device and a storage medium. According to the method, the chip product is modeled by using a neural network based on a slice sequence of the chip product in advance to obtain a three-dimensional stereoscopic model. When the chip products are compared, a comparison feature is acquired responsive to an operation of a user. For each chip product, a comparison result corresponding to the comparison feature is acquired from the three-dimensional stereoscopic model corresponding to each chip product. Then, the comparison result corresponding to each chip product is displayed.

An image processing method and apparatus, a device, and a storage medium are provided. The image processing method includes: obtaining key points of a reference region of an object in an image; determining the orientation of the reference region according to the key points of the reference region; and performing deformation processing on a region to be adjusted of the object based on the orientation of the reference region, where the region to be adjusted is the same as or different from the reference region.