A computing system and a method for calibration verification is presented. The computing system is configured to perform a first calibration operation, and to control a robot arm to move a verification symbol to a reference location. The robot control system further receives, from a camera, a reference image of the verification symbol, and determines a reference image coordinate for the verification symbol. The robot control system further controls the robot arm to move the verification symbol to the reference location again during an idle period, receives an additional image of the verification symbol, and determines a verification image coordinate. The robot control system determines a deviation parameter value based the reference image coordinate and the verification image coordinate, and whether the deviation parameter value exceeds a defined threshold, and performs a second calibration operation if the threshold is exceeded.

Surgical kit inspection systems and methods are provided for inspecting surgical kits having parts of different types. The surgical kit inspection system comprises a vision unit including a first camera unit and a second camera unit to capture images of parts of a first type and a second type in each kit and to capture images of loose parts from each kit that are placed on a light surface. A robot supports the vision unit to move the first and second camera units relative to the parts in each surgical kit. One or more controllers obtain unique inspection instructions for each of the surgical kits to control inspection of each of the surgical kits and control movement of the robot and the vision unit accordingly to provide output indicating inspection results for each of the surgical kits.

The image processing device according to the invention includes: a first acquisition unit to acquire a captured image; a display control unit to display a setting screen to allow to user to set an image processing area, which is an area where predetermine image processing is performed, in the image acquired by the first acquisition unit on a display device; and a second acquisition unit configured to acquire movable range information indicating a movable range of a working device, operations of which are controlled on the basis of a result of the predetermined image processing. The display control unit controls the display of the setting screen so as to cause the user to identify a range in which the working device is not able to operate in the image, on the basis of the movable range information acquired by the second acquisition unit.

A method of structural masking for progressive health monitoring of a structural component includes receiving a current image of the structural component. A processor aligns the current image and a reference image of the structural component. The processor performs a structure estimation on the current image and the reference image to produce a current structure estimate image and a reference structure estimate image. The processor generates a structural mask from the reference structure estimate image. The processor masks the current structure estimate image with the structural mask to identify one or more health monitoring analysis regions including a potential defect or damaged area appearing in the masked current structure estimate image that does not appear in the reference structure estimate image.

A system and method of detecting damage to a component may include a first sensor and a processor. The method may include the steps of receiving, by the processor, a first data for the component from a first sensor, aligning, by the processor, the first data with a reference model, determining, by the processor, a feature dissimilarity between the first data and the reference model, classifying, by the processor, the feature dissimilarity, and determining, by the processor, a probability that the feature dissimilarity indicates damage to the component.

There are included a probe that can be arranged in an imaging field of view, a horizontal drive section for causing the probe to contact a side surface of a workpiece on a stage, a display section for displaying a model image, a contact position designation section for receiving designation of contact target position information in the model image, a characteristic amount information setting section for setting characteristic amount information, a measurement setting information storage section for storing a plurality of pieces of contact target position information and the characteristic amount information, and a measurement control section for identifying a position and an attitude of the workpiece from a workpiece image by using the characteristic amount information, for identifying a plurality of contact target positions on the side surface of the workpiece where the probe should contact, based on the identified position and the identified attitude of the workpiece.

A machine vision system for automatically identifying and inspecting objects is disclosed, including composable vision-based recognition modules and a decision algorithm to perform the final determination on object type and quality. This vision system has been used to develop a Projectile Identification System and an Automated Tactical Ammunition Classification System. The technology can be used to create numerous other inspection and automated identification systems.

A method for evaluating a turbine component includes inducing a thermal response of the component at an initial time, capturing a two-dimensional infrared image of the thermal response of the component with a thermal imaging device, wherein the two-dimensional infrared image comprises a plurality of infrared image pixels, generating a two-dimension to three-dimension mapping template to correlate two-dimensional infrared image data with three-dimensional locations on the component, mapping at least a subset of the plurality of infrared image pixels of the two-dimensional infrared image to three-dimensional coordinates using the mapping template, and generating a three-dimensional infrared image and infrared data of the component from the mapped infrared image pixels to three-dimensional coordinates, wherein the three-dimensional infrared image and infrared data is used to qualify the component for use.

A workpiece inspection device 1 includes a table (3), image capturing unit fixing part (7), first light projection unit (4), second light projection unit (5), linear movement mechanism (8), turning mechanism (9), quality determination unit (10), and control unit (11). The control unit (11) performs first image capturing step of causing first light projection unit (4) to project light and causing image capturing unit (6) to capture image, detailed inspection portion-determination step of setting, portion of workpiece (2) determined to require detailed inspection based on image captured in the first image capturing step, second image capturing step of causing second light projection unit (5) to project light onto the workpiece (2) and causing image capturing unit (6) to capture image of the detailed inspection-requiring portion, and quality determination step of determining quality of the detailed inspection-requiring portion based on image captured in the second image capturing step.

Various embodiments of the present technology generally relate to unmanned aerial vehicle (UAV) scale rendered analysis, orthomosaic, and 3D mapping and landing platform systems. More specifically, some embodiments relate to systems, methods, and means for the collection and processing of images captured during a UAV flight sequence. In some embodiments, the UAV landing platform retrieves flight information and initial map information over a unidirectional virtual private network from a multitenant cloud-based scheduling application. The UAV landing platform sends the initial map information to a UAV over a WiFi, Bluetooth, or radio frequency network and initiates a drone flight sequence once the drone flight sequence has been approved by a local user. The UAV landing platform receives property image data from a UAV after a UAV flight sequence has ended and transmits the received property image data back to the cloud application.