A device to detect defects in a finished surface by analyzing images thereof includes a supporting mechanism, a transmitting mechanism, a detecting mechanism, and a processor. The transmitting mechanism carries and transmits the product. The detecting mechanism includes a detecting frame, and a light source assembly. The processor is used to connect to a camera assembly, and preprocess image obtained of the front of the product to obtain a detection of any defects of the front of the product.

An inspection system for a fabricated object formed by layering powder includes an acquisition unit that acquires an image of a surface of each of layers, an identification unit that identifies a defect portion (protruding portion or recessed portion) on the surface of the powder and a position of the defect portion based on the acquired image, and a determination unit that determines that an abnormality occurs when the defect portion successively occurs at a same position in the plurality of layers.

A system for taking high-resolution photographs from a vehicle-mounted camera, forming orthomosaics from video and/or multiple high-resolution photographs, and using artificial intelligence to detect and classify pavement flaws and defects in the imagery. Detection also includes the ability to capture quantifiable metrics for the defects and/or a region of interest. Three-dimensional imagery is produced from the same images as the orthomosaics. Surface and terrain map products made from the same source images capture additional details such as depth and volume. The highlighted orthomosaics and three-dimensional imagery can then be used as a basis to determine the pavement surface condition and subsequently support maintenance orders and manage pavement repairs. Further, metadata such as latitude, longitude, and altitude geo-location coordinates and sampling time can also be transferred to the output products to create a digital time history and enable analysis for preventative maintenance planning. Alternatively-sourced imagery may also be analyzed.

A method of automatically setting optical parameters, using Automatic Optical Inspection (AOI) System, the method includes: obtaining a recommended object image when the AOI system under a first recommended optical parameter set; performing computation on a standard image of a and a recommended image of the to-be-measured object according to an optimized error function to obtain a recommended error value between the standard image and the recommended image; determining whether the recommended error value converges, when determining that the recommended error value does not converge, performing computation according to the recommended error value and first recommended optical parameter set to obtain a second recommended optical parameter set; when the recommended error value converges, deciding the first recommended optical parameter set as the best optical parameter set of the AOI system.

An optical system includes an illumination module configured to illuminate a sample object with at least one angle-variable illumination geometry. The optical system includes an imaging optical unit configured to produce an imaged representation of the sample object that is illuminated with the at least one angle-variable illumination geometry on a detector. The optical system includes the detector, which is configured to capture at least one image of the sample object based on the imaged representation. The optical system includes a controller configured to determine a result image based on a transfer function and the at least one image. A method includes illuminating a sample object with at least one angle-variable illumination geometry, imaging the sample object on a detector, based on the imaged representation, capturing at least one image of the sample object, and, based on a transfer function and the at least one image, determining a result image.

A system includes a first sensor having a fixed location relative to a workspace, a second sensor, at least one robotic manipulator coupled to a manipulation tool, and a control system in communication with the at least one robotic manipulator. The control system is configured to determine a location of a workpiece in the workspace based on first sensor data from the first sensor and a three-dimensional (3D) model corresponding to the workpiece. The control system is configured to map a set of 2D coordinates from a second 2D image from the second sensor to a set of 3D coordinates based on the location, and to generate one or more control signals for the at least one robotic manipulator based on the set of 3D coordinates.

An inspection system for a vehicle underbody in an in-line process includes: a vehicle recognition unit for acquiring a vehicle ID by recognizing a vehicle entering an inspection process; a vision system that photographs the vehicle underbody through a plurality of cameras disposed under a vehicle moving direction (Y-axis) and disposed at vertical and diagonal angles along a width direction (X-axis) of the vehicle; and an inspection server that detects assembly defects of a component by performing at least one of a first vision inspection that matches an object image for each component through a rule-based algorithm or a secondary deep-learning inspection through a deep-learning engine by acquiring a vehicle underbody image photographed by operating the vision system with setting information suitable for a vehicle type and a specification according to the vehicle ID.

Provided is a system and method for visual inspection. The system may be used in a quality assurance station at a manufacturing facility or site. The system may evaluate and determine the quality of manufactured or fabricated articles. The system may include a mechanical subsystem for capturing images of the article. The system may include a sensor such as a camera for capturing data, such as images. The system may include an artificial intelligence system to determine if the article suffers from an impermissible defect.

A method and an apparatus for detecting a defect based on a phased pass/fail determination are disclosed. According to at least one aspect of the present disclosure, a method comprising: a process of acquiring a product image which is an image of the product; a first determination process of inputting the product image into a first determination model to perform a pass/fail determination for the product; and a second determination process of inputting the product image into a second determination model to perform a pass/fail determination for the product when the product is determined to be undeterminable as a result of the pass/fail determination of the first determination process.

A bale monitoring system includes an imaging device that is operable to capture a stereoscopic image of a bale. A computing compares the stereoscopic image of the bale to a three-dimensional standard to identify a deviation of the bale from the three-dimensional standard. The computing device may then assign the bale a shape quality score based on the deviation of the bale from the three-dimensional standard. The shape quality score may indicate a magnitude of the deviation of the bale from the three-dimensional standard. Additionally, the stereoscopic image may be analyzed to identify characteristics of the bale, such as a broken wrap material or an improperly formed bale.