Abstract: Machine learning-based systems are described for automatically generating an inspection recipe that can be utilized when inspecting web materials, sheet parts or other products for defects. One example method for generating an inspection recipe includes assigning, by processing circuitry, a pseudo-label to each image of a plurality of images based on the content of the image and a labeling model, and storing the pseudo-labeled images in a second set of images; extracting, by the processing circuitry, one or more features from each image of the plurality of images, and storing the one or more features as a feature list for the image; generating, by the processing circuitry, a decision tree based on the second set of images and the feature lists of the second set of images; generating, by the processing circuitry, an inspection recipe based on the decision tree, the inspection recipe comprising a plurality of classification rules; and outputting the inspection recipe.

Abstract: Techniques are described for inspection of films in order to detect Machine Direction Line (“MDL”) defects. An example system comprises a light source configured to provide a source of light rays, directed to a film product so that the light rays are incident to a surface of the film product at a non-perpendicular angle of incidence. An image capturing device is configured to generate an image of the film product by capturing a level of light intensity of the light rays exiting the film product in a plurality of image areas, each image area representing a line imaged across the film product that is perpendicular to a direction of manufacture of the film product. An image processing device is configured to process the image of the film product to provide an indication of the detection of one or more machine direction line (MDL) defects in the film product.