A dental CAD/CAM application generates a 3D model representing a patient's dental anatomy. This model may be a 3D surface. The surface may also be textured with either a monochrome or color image superimposed. The display routine that is used to display the 3D model is enhanced to adjust the contrast in the region of a displayed mouse pointer (or other input device) as a user explores the display image. When this feature is activated and the mouse pointer positioned, preferably the texturing on the 3D model is recomputed in that local area and redisplayed showing greater contrast and detail. Preferably, the contrast is increased from a center to an edge of the area of contrast. Having the texturing of the model being improved and highlighted around the margin is desirable, as it allows the user to see more easily where the margin is located.

In an example, a method includes capturing one or more friction ridge images of a finger at an instance in time, the one or more friction ridge images including a plurality of perspectives of the finger. The method also includes determining, from the one or more friction ridge images, a rolled fingerprint representation of the finger, the rolled fingerprint representation comprising data from the plurality of perspectives, and outputting the rolled fingerprint representation.

An otoscope may project a temporal sequence of phase-shifted fringe patterns onto an eardrum, while a camera in the otoscope captures images. A computer may calculate a global component of these images. Based on this global component, the computer may output an image of the middle ear and eardrum. This image may show middle ear structures, such as the stapes and incus. Thus, the otoscope may see through the eardrum to visualize the middle ear. The otoscope may project another temporal sequence of phase-shifted fringe patterns onto the eardrum, while the camera captures additional images. The computer may subtract a fraction of the global component from each of these additional images. Based on the resulting direct-component images, the computer may calculate a 3D map of the eardrum.

Disclosed is a system, method, and devices as system elements to recognize an object by an object recognizing system including an imaging device and a moving assembly to move the imaging device around the object, to form a certified visual model of the object to be recognized. Especially the disclosure relates to gemstone imaging by an imaging method including photographing a target, in an illumination, by a camera, to obtain at least one image of the targeted object to be recognized.

The present disclosure provides a security control method and device of an application, and an electronic device. The method includes: determining whether running information of the application meets a preset security control condition; calling a preset service if the running information of the application meets the preset security control condition, the preset service being configured to enable the application to run in a trusted execution environment; and executing an authentication service corresponding to the running information of the application in the trusted execution environment.

An optoelectronic device includes a semiconductor substrate, an array of optical emitters arranged on the substrate in a two-dimensional pattern, a projection lens and a diffractive optical element (DOE). The projection lens is mounted on the semiconductor substrate and is configured to collect and focus light emitted by the optical emitters so as to project optical beams containing a light pattern corresponding to the two-dimensional pattern of the optical emitters on the substrate. The DOE is mounted on the substrate and is configured to produce and project multiple overlapping replicas of the pattern.

A method of visual odometry for a non-transitory computer readable storage medium storing one or more programs is disclosed. The one or more programs includes instructions, which when executed by a computing device, causes the computing device to perform the following steps comprising: performing data alignment among sensors including a LiDAR, cameras and an IMU-GPS module; collecting image data and generating point clouds; processing, in the IMU-GPS module, a pair of consecutive images in the image data to recognize pixels corresponding to a same point in the point clouds; and establishing an optical flow for visual odometry.

Apparatus, methods, and other embodiments associated with a key duplication machine are described. In one embodiment, an assembly for duplicating a master key includes an optical imaging device, a logic, a clamping assembly, and a cutting member. The optical imaging device is capable of capturing an optical image of at least a portion of the master key. The logic is capable of determining a key pattern of the master key from the optical image of the master key. The clamping assembly is capable of clamping a key blank and the cutting member is capable of cutting a key pattern into said key blank.

A human-following robot for searching a following target when failing to track the following target includes a location estimating module configured to estimate a location of the following target based on map information and trajectory information, a search range setting module configured to set a search range of the following target based on the estimated location information and human walking pattern information, and tracking module configured to track the following target after moving to the search range. Since the robot estimates a location of a missed following target and the moves to the estimated location by utilizing map information and human walking pattern information including walking pattern data of persons in a surrounding environment, which is accumulated during a predetermined period, the following target may be detected again.

A three-dimensional (3D) image recognition system includes a first imaging sensor capable of collecting a first wavelength range of light and a second imaging sensor capable of collecting a second wavelength range of light. The first imaging sensor and the second imaging sensor are placed apart. The 3D image recognition system also includes a processor configured to identify at least one landmark area of a first image of an object collected by the first imaging sensor, and identify at least one matching landmark area in a second image of the object collected by the second imaging sensor. The processor is further configured to extract the 3D information of the object from the at least one landmark area of the images collected.