A low cost surface strain measurement system using image processing for sheet metal forming applications

Abstract Circle and square grid methods are widely used for strain analysis in sheet metal forming operations. In the current paper, images of the deformed grids are captured using a low-cost generic USB microscope and analyzed using an image processing algorithm for automatic strain measurement. The images of the deformed circular grid are analyzed using the segmentation approach, arc support line detection algorithm, and least squared error-ellipse fitting algorithm. In case of the deformed square grids, the corners of the quadrilateral are found using Hough Transform (HT) with clustering and are used to fit the maximum size ellipse inside the quadrilateral by projective collineation method. The effectiveness of different algorithms in measurement has been discussed. Good agreement was found between the results obtained from experiments and simulations in LS-Dyna software. The software is able to measure the strain with a maximum error of 1.933 % and 2.11 % for circular and square grids, respectively.