This invention provides a processing apparatus for determining a state of secular change of a deformation of a construction, comprising a selection unit that selects, as a target for determination of secular change, at least a portion of deformations from among a plurality of deformations included in a first image at a first time period, on the basis of at least one of information relating to deformations, information relating to the construction, user selection, or a shape and a relative positional relationship of two or more deformations; a first determination unit that determines a deformation corresponding to a selected deformation among a plurality of deformations included in a second image at a second time period; and a second determination unit that determines a state of secular change between a selected deformation and a deformation determined by the first determination unit.

A visual inspection apparatus detects a defect candidate for each of captured images of a crown surface of a piston that are captured at a plurality of posture angles different from one another, locates a three-dimensional position of the defect candidate based on a two-dimensional position of the defect candidate detected from at least one captured image among the captured images captured at the plurality of posture angles, applies a perspective projection transformation on the three-dimensional position of the defect candidate to acquire a two-dimensional position of the defect candidate for each of the captured images captured at the plurality of posture angles, determines a feature amount regarding the defect candidate based on the two-dimensional position of the defect candidate for each of the captured images captured at the plurality of posture angles, and inspects the crown surface of the piston using the feature amount regarding the defect candidate.

There is provided a system and method of examining a specimen. The method comprises obtaining an actual measurement in response to scanning the specimen using a set of scanning parameters with predefined values; obtaining a simulated measurement based on design data; comparing the actual measurement with the simulated measurement to identify a deviation with respect to a predefined tolerance; identifying at least one structural property as root cause of the deviation by: obtaining one or more additional actual measurements in response to scanning the specimen using one or more varying values of at least one scanning parameter; and providing the actual measurement and the additional actual measurements to a simulation model representative of simulated measurement distribution in a multi-dimensional property space characterized by the structural properties of the plurality of layers and the at least one scanning parameter, thereby identifying the at least one structural property.

According to various embodiments, techniques and mechanisms are provided to enhance damage detection for objects such as vehicles in vehicle tunnels. In some implementations, a striped lighting tunnel is configured with cameras for capture of object or vehicle surface images when illuminated by striped lighting in a vehicle tunnel. Multiple vehicle surface images may be captured from a variety of perspectives. The vehicle surface images illuminated by striped lighting can be analyzed potentially with a vehicle object model. Each vehicle object model may include numerous object model components. Damage may be determined using striped lighting illuminated vehicle surface images to identify the type, likelihood, and extent of damage.

According to various embodiments, techniques and mechanisms are provided to improve striped lighting damage detection. In some implementations, a striped lighting tunnel is configured with cameras for capture of object or vehicle surface images when illuminated by striped lighting and when illuminated by uniform panel lighting. The vehicle surface images may be captured from a variety of perspectives. The vehicle surface images can be analyzed to generate vehicle object models or can be analyzed by using these vehicle object models. Damage may be determined using the vehicle surface images to identify the type, likelihood, and extent of damage.

According to various embodiments, techniques and mechanisms are provided to enhance damage detection and assessment for objects such as vehicles. In some implementations, a striped lighting tunnel is configured with cameras for capture of object or vehicle surface images when illuminated by striped lighting. The vehicle surface images may be captured from a variety of perspectives. Damage assessed is mapped to multiple views of a vehicle. In some embodiments, a damage likelihood score is generated and if the damage likelihood score reaches a threshold, a heatmap visual representation may be generated and included in one or more views to present the type, likelihood, and extent of damage.

According to various embodiments, a variably switched striped lighting pattern panel is provided. A panel may include numerous rows of light emitting diodes (LEDs). Alternating rows are controlled separately by a microcontroller so that a first set can be switched on while a second set switched off to provide striped lighting. On the other hand, both sets can be switched on to provide for uniform lighting. Barriers may be provided between the rows of LEDs while a diffuser is placed in front of the LEDs. The variably switched striped lighting pattern panels can be used in a vehicle tunnel in a variety of configurations to allow for vehicle image capture in varying conditions for damage assessment.

According to various embodiments, techniques and mechanisms are provided to enhance damage detection for objects such as vehicles. In some implementations, a striped lighting tunnel is configured with cameras for capture of object or vehicle surface images when illuminated by striped lighting. The vehicle surface images may be captured from a variety of perspectives. Striped lighting capture may be implemented using gaps between uniform lighting panels and the uniform lighting panels themselves, along with high speed cameras capable of taking more than 120 frames per second. The gap width between uniform lighting panels may be determined using an inverse relationship with frame rate. Damage may be determined using striped lighting illuminated vehicle surface images to identify the type, likelihood, and extent of damage.

A product inspection system includes a spectrum measurer that measures a spectrum of a product being conveyed, and a quality determiner that determines quality of the product on the basis of output obtained by inputting spectral data of the product measured by the spectrum measurer into a trained model generated by machine learning. The trained model is generated by machine learning using training data including spectral data measured in mutually different postures.