A method of inspecting images on printed products by a computer in a printing machine. Printed products are recorded and digitized by an image sensor of an image inspection system in the course of the image inspection process, and the computer compares them to a digital reference image. If deviations are found, the defective printed products are removed. The computer analyzes the deviations found in the course of the image inspection process together with further data from other system parts and from the machine, determines specific defect classes and the causes thereof based on the defects by machine learning processes, assigns the defects found in the image inspection process to the defect classes in a corresponding way, and displays the classified detected defects with their defect classes and causes to an operator of the machine so that the operator can initiate specific measures to eliminate the defect causes.

Systems and methods are disclosed for detecting defects during manufacturing processes for materials and products. The provided systems may utilize imaging units and computer detection algorithms to determine the presence or absence of defects in manufactured materials or products. Detection of defects in material or products by the disclosed systems may prompt intervention in the manufacturing process to correct the source of the defects.

A system for inspecting and validating processes performed on a continuous web of fabric in an automated apparel manufacturing environment. The continuous web of fabric can move in a step wise fashion across a work area where tooling can perform one or more processes on the continuous web of fabric. At least one projector is provided to display an image onto the continuous web of fabric the image including a first image related to an article to be manufactured and a second image related to a reference grid. The continuous web of fabric and the first and second images are viewed by a camera, and data related to the viewed first and second images and the continuous web of fabric can be sent to a computer implemented control center which can analyze the data to determine whether a deviation or error exists regarding the manufacturing process.

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.

The present disclosure provides systems and methods for calibration. In one example, the method may comprise optical image analysis for calibration. The method may comprise generating an optical projection of one or more calibration features onto a material surface provided in a material fabrication or processing machine, and determining one or more spatial characteristics of the calibration features. The one or more spatial characteristics may comprise a distance, a position, an orientation, an alignment, a size, or a shape of one or more calibration features. The one or more spatial characteristics may be used to adjust at least one of (i) a position or an orientation of an imaging unit relative to the material surface and the material fabrication or processing machine, (ii) an angle or an inclination of the material surface relative to the imaging unit, and (iii) one or more imaging parameters of the imaging unit.

Systems and methods for on-loom detection of faults in fabric. An image-capture trigger-mechanism triggers an imaging device to capture a first image of a section of the weaving area at a first instant during each weft insertion cycle and a second image of the section of weaving area may be captured at a second instant during each weft insertion cycle. The images may be timed to provide images of the warp yarns and the weft yarns at optimal instants during the weft insertion cycle. An image processor detects irregularities in the data received from the imaging device

Illumination modules (530) are described for use during manufacturing processes and subsequent material processing steps. The illumination modules (530) may assist with implementing methods for performing quality assurance or defect detection while material (510) is being manufactured or processed. Methods are also described for utilizing an illumination module to facilitate the detection of material properties or conformations as a part of quality assurance or defect detection algorithms.

A method for characterizing the uniformity of a material includes selecting a set of size scales at which to measure uniformity within an area of interest in an image of the material; suppressing features in the image smaller than a selected size scale of interest within the set of size scales; dividing the image into patches equal to the size scale of interest; and calculating a uniformity value within each patch.

A system for inspecting and validating processes performed on a continuous web of fabric in an automated apparel manufacturing environment. The continuous web of fabric can move in a step wise fashion across a work area where tooling can perform one or more processes on the continuous web of fabric. At least one projector is provided to display an image onto the continuous web of fabric the image including a first image related to an article to be manufactured and a second image related to a reference grid. The continuous web of fabric and the first and second images are viewed by a camera, and data related to the viewed first and second images and the continuous web of fabric can be sent to a computer implemented control center which can analyze the data to determine whether a deviation or error exists regarding the manufacturing process.

A method of synchronizing a line scan camera. The method comprises: obtaining line scan data of a region of interest (ROI) of a travelling surface from the line scan camera, the line scan camera being oriented perpendicular to a direction of travel of the travelling surface, the line scan data comprising a plurality of lines; identifying occurrences of a major frequency of a repeated texture on the travelling surface using characterized line scan data for each line in the plurality of lines of the line scan data; determining a period of the major frequency; and changing a line rate of the line scan camera when the determined period is different than a reference period.