About the Flaw Detection Tools

The Flaw Detection Vision Tools are composed of two groups of tools, the SurfaceFlaw function and the DetectFlaw, FlexFlawModel and TrainFlawModel functions.

SurfaceFlaw Flaw Detection Vision Tool

The SurfaceFlaw function is designed to detect areas of local intensity and color variations which are flaws in the production process. The function uses an internal filtering operation to first highlight edges and areas with sudden color or greyscale variations, before applying blob analysis to determine whether or not flaws are present.

SurfaceFlaw is a stand-alone function, and does not require the use of a model, simplifying its setup and improving its execution time. Due to not incorporating a model, the function is able to account for run-time lighting variations and accurately detect flaws. However, it does not have the ability to compensate for possible variations, as the DetectFlaw, FlexFlawModel and TrainFlawModel functions can, so it can not adjust for process variations in a part. Therefore, SurfaceFlaw is best suited to applications where a part should have a uniform area to be inspected, such that any sudden change in intensity will be classified as a defect. If the part will have intensity variations, the other Flaw Detection functions should be able to account for the variations.

Note: The SurfaceFlaw function does accept a Mask data structure output by the Mask function. This allows the function to only inspect specified areas within an image. For more information, see Mask.

DetectFlaw, FlexFlawModel and TrainFlawModel Flaw Detection Vision Tools

The DetectFlaw, FlexFlawModel and TrainFlawModel Flaw Detection Tools are designed to perform advanced pattern matching analysis, verifying whether or not defects are present. The functions combine model "stretching" (teaching the function to compensate for possible variations) and image subtraction to create detailed models that are compared against acquired images, determining whether a defect exists in the acquired image. Within this architecture, the functions provide the ability to dynamically update the model during run-time.

The functions, when combined together, are capable of performing the following types of inspections:

Boundary Defects: Ensuring that the part/object maintains the same shape.
Surface Defects : Ensuring that the part/object does not have any stains or scratches.
Print Inspections: Ensuring that the part/object's silk screened logo was printed correctly and without defects.