Systems, methods, storage media, and computing platforms for scanning items at the point of manufacturing are disclosed. Exemplary implementations may: receive a first set of images of an item from a first set of camera sources; detect a code in the first set of images; combine, responsive to detecting the code, along a second axis perpendicular to the first axis, the first set of images into a first set of combined images; rotate parallel to the first axis; and combine along the first axis.

A method of analyzing a product includes performing an anomaly detection on a received image using an autoencoder, wherein the autoencoder includes at least one first neural network trained based on a first set of training images, and the first set of training images includes a plurality of training images each showing a corresponding defect-free product; determining, using a binary classifier, whether or not a defect is present based on a result of the anomaly detection; performing defect detection on the received image using a defect detector, wherein the defect detector includes a third neural network trained based on a one third set of training images, and the third set of training images includes a plurality of training images each showing a corresponding defective product; and evaluating a result based on a weighting of the results of the anomaly detection, the defect detection, and the binary classifier.

A displacement meter that measures displacement of an object includes a calculation circuit which calculates a displacement amount of the object using a cross-correlation function of plural images detected at different timings by a photoelectric conversion element array. The calculation circuit performs a Fourier transform on the images, applies a band-pass filter to the images having undergone the Fourier transform, and calculates the cross-correlation function using the images to which the band-pass filter has been applied. Assuming that a magnification of a light-receiving optical assembly is M, the number of pixels in the photoelectric conversion element array is N, and a pixel pitch is P (um), a low cut-off frequency HPF of the band-pass filter and a high cut-off frequency LPF of the band-pass filter satisfy: 3M/(N×P)≤HPF≤10M/(N×P), 40M/(N×P)≤LPF≤60M/(N×P).

A worker constructs a map necessary for inspection of infrastructure equipment using data acquired using a target imaging device as data necessary for map generation, thereby reducing the cost necessary for transportation and the like of an autonomous inspection apparatus, and moreover, travel evaluation and inspection evaluation are performed using an evaluation function, and a map necessary for the inspection can be corrected based on a travel route of an autonomous travel route and an inspection result based on an evaluation result, whereby the introduction cost can be reduced.

A computer-based system and method for taking clarity measurements of a gem, and a computer-readable medium having computer-executable instructions, are provided and include receiving a pixilated image of a gem and identifying pixels representing an inclusion. The method and medium further include determining characteristics of the inclusion as a function of the pixels representing the inclusion, and providing a clarity grade based upon the determined characteristics. Also provided is a method for mapping a gem, and a computer-readable medium having computer-executable instructions, which include receiving a pixilated image of a gem having facet edges, and identifying pixels representing the facet edges. The method and medium further include generating a diagram of the gem, such that the diagram is a function of the pixels representing the facet edges, and superimposing the diagram onto the pixilated image.

A method for detecting defects in a formed metal part includes locating one or more regions of interest in a synthetic image of a part manufactured by a forming process. The synthetic image is informed based on a physics-based simulation of the forming process. The regions of interest indicate a high risk of having a defect from the forming process. A set of training images including real images of actual manufactured parts are registered with the synthetic image. The regions of interest are overlaid on each training image, to extract patches from the training images that correspond to high-risk regions. An anomaly detection model is trained on the patches extracted from the training images to detect a defect in a formed metal part from an acquired image of the formed metal part, by detecting an anomaly in a patch extracted from the acquired image that corresponds to a high-risk region.

The invention provides an automatic inspection process for detecting visible defects on a manufactured item. The process includes a set up mode in which images of same-type defect free items, but not images of same-type defected items, are obtained, and an inspection mode in which images of both same-type defect free items and same-type defected items, are obtained and defects are detected. Images of the same-type defect free items are analyzed and based on the analysis the process switches to the inspection mode.

This invention provides a system and method for displaying color match information on an acquired image of an object. A model/pattern having a plurality of color test points at locations of stable color is provided. A display process generates visible geometric shapes with respect to the color test points in a predetermined color. An alignment process aligns features of the object with respect to features on the model so that the geometric shapes appear in locations on the object that correspond to locations on the model. The geometric shapes can comprise closed shapes that surround a region expected to be stable color on the object. Such shapes can define circles, squares, diamonds or any other acceptable closed or open shape that is visible to the user on the display.

An image detection obtains original image. The original image is corrected to obtain a corrected image. Median filtering is performed on the corrected image to obtain a filtered image. A contrast of the filtered image is adjusted to obtain an adjusted image. Bilateral filtering is performed on the adjusted image to obtain an enhanced image. Defects in the enhanced image is detected. The method can detect defects in images accurately and efficiently.

This invention provides an easy-to-manufacture, easy-to-analyze calibration object which combines measurable and repeatable, but not necessarily accurate, 3D features—such as a two-sided calibration object/target in (e.g.) the form of a frustum, with a pair of accurate and measurable features, more particularly parallel faces separated by a precise specified thickness, so as to provide for simple field calibration of opposite-facing DS sensors. Illustratively, a composite calibration object can be constructed, which includes the two-sided frustum that has been sandblasted and anodized (to provide measurable, repeatable features), with a flange whose above/below parallel surfaces have been ground to a precise specified thickness. The 3D corner positions of the two-sided frustum are used to calibrate the two sensors in X and Y, but cannot establish absolute Z without accurate information about the thickness of the two-sided frustum; the flange provides the absolute Z information.