An AR scenario-based gesture interaction method, a non-transitory computer-readable medium, and a wireless communication terminal. The method includes: collecting a RGB image, a depth image, and corresponding IMU data of a current frame; obtaining posture information and hand information of the current frame by processing the RGB image, the depth image, and the IMU data; obtaining three-dimensional point cloud information of a hand in a reference coordinate system by performing three-dimensional dense modeling based on the posture information and the hand information of the current frame; obtaining pose information of a virtual object in the reference coordinate system; and obtaining an occlusion relationship between the hand and the virtual object by rendering the hand and the virtual object based on the three-dimensional point cloud information of the hand, the pose information of the virtual object, and preset point cloud information of the virtual object in the reference coordinate system.

A swingable solar electric heater comprises an electric heater structure including a head swing element, a heating element, a timer, a base, and a safety dump switch. The head swing element is used to swing back and forth to perform radiant heating within a fixed angle, the timer is connected to the heating element, and the safety dump switch is used to turn off the heating element when the tilt angle of the base exceeds a limit. A current capture device captures the image data of the scene where the electric heater structure is located to obtain and output the corresponding current scene image. An early warning control device is used to extract each pixel value of each pixel in the current scene image, to calculate the standard deviation in the current scene image, and to send a blockage warning signal when the standard deviation exceeds a limit.

A method of filtering a fingerprint image is provided. The method includes: receiving an input fingerprint image; preliminarily filtering the input fingerprint image to obtain a preprocessed image; normalizing and then filtering the preprocessed image to obtain a denoised image; filtering and then segmenting the preprocessed image to obtain a background mask; postprocessing the background mask to obtain a final mask; and applying the final mask to the denoised image to obtain an output fingerprint image.

Aspects of the present disclosure relate to QCFA deblurring. An example method includes obtaining an image to be processed and determining an average of pixel values between a first one or more pixels and a second one or more pixels of the image. The second one or more pixels neighbor the first one or more pixels. The method also includes determining a difference between pixel values of the first one or more pixels and the second one or more pixels, generating one or more weights based on the average and the difference, and combining the average and the difference based on the one or more weights to generate a deblurred pixel value. A processed image includes one or more deblurred pixel values.

A method for vehicle parking detection, a system for vehicle parking detection, an electronic device and a storage medium are disclosed. The method includes: obtaining a first lateral distance between a vehicle and a reference object in a site by a first distance sensor; obtaining a second lateral distance between the vehicle and the reference object by a second distance sensor; collecting a first scene image by a first camera, and obtaining a first longitudinal distance based on the first scene image, the first longitudinal distance being a distance between a first mark line on the vehicle and a first parking line in the site; and determining whether the vehicle is parked at a target location in the site based on the first lateral distance, the second lateral distance and the first longitudinal distance.

This application discloses an inspection method and an inspection machine for a display panel. The inspection method includes the steps of: taking a picture of a to-be-inspected display panel to obtain a to-be-inspected image of the to-be-inspected display panel; removing high-frequency information in the to-be-inspected image to obtain a high-frequency-removed image; calculating a difference between the to-be-inspected image and the high-frequency-removed image to obtain a difference image; making a determination regarding the difference image by comparing the difference image with a preset threshold, determining that the display panel fails the inspection if the difference image exceeds the preset threshold, and determining that the display panel passes the inspection if the difference image does not exceed the preset threshold.

Embodiments disclose systems and methods that aid in screening, diagnosis and/or monitoring of medical conditions. The systems and methods may allow, for example, for automated identification and localization of lesions and other anatomical structures from medical data obtained from medical imaging devices, computation of image-based biomarkers including quantification of dynamics of lesions, and/or integration with telemedicine services, programs, or software.

Disclosed are methods for identification and quantification of a number of different materials within an object using one or more multi-energy CT imaging devices and the image data sets produced therefrom. Identification and quantification of different materials is achieved by using the following three properties: solve only for sparse solutions; separate the soft tissue problem from the dense material problem; and use a combinatorial approach to allow for simple application of different constraints to different combinations of materials. Also disclosed are one or more computer program products, computer systems or computer implemented methods for the identification of multiple materials within an object.

A system for obtaining dark current images includes one or more processors and one or more hardware storage devices storing instructions that are executable by the one or more processors to configure the system to perform various acts. The acts include obtaining a first image frame, generating a first low-pass filtered image by applying a low-pass filter to the first image frame, and generating a first estimated dark current image by subtracting the first low-pass filtered image from the first image frame.

A system for detection and identification of objects and obstacles near, between or on railway comprise several forward-looking imagers adapted to cover each different range forward and preferably to be sensitive each to different wavelength of radiation, including visible light, LWIR, and SWIR. The substantially homogeneous temperature along the rail the image of which is included in an imager frame assists in identifying and distinguishing the rail from the background. Image processing is applied to define living creature in the image frame and to distinguish from a man-made object based on temperature of the body. Electro optic sensors (e.g. thermal infrared imaging sensor and visible band imaging sensor) are used to survey and monitor railway scenes in real time.