1991
DOI: 10.1063/1.1142484
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Measurement of microdisplacements by machine vision photogrammetry (DISMAP)

Abstract: An image processing system is described for use in micromechanics research on materials, such as for determining the displacements and strains surrounding crack tips. This vision system is a machine implementation of the stereoimaging technique that was developed for making submicron measurements of displacements under high resolution conditions. It uses a Cognex 2000 image processing system, cameras to obtain digital images from analog photographs, a graphics display terminal and track ball for operator inter… Show more

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Cited by 79 publications
(30 citation statements)
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“…[14] The DISMAP technique was used to characterize the cracktip displacement fields. The crack-tip displacement fields were then used to compute the near-tip strain fields.…”
Section: Methodsmentioning
confidence: 99%
“…[14] The DISMAP technique was used to characterize the cracktip displacement fields. The crack-tip displacement fields were then used to compute the near-tip strain fields.…”
Section: Methodsmentioning
confidence: 99%
“…Micrographs of the same near-tip region at the unloaded and loaded conditions constitute a stereo pair that was analyzed using a vision-based steroimaging technique that measures the displacement and strain field near the crack tip. [42,43] The SEM fractography was performed on several specimens that fractured during in-situ fracture testing before the entire series of K levels was applied. Seven specimens remained intact after in-situ fracture testing to K levels of 32 to 70 MPa ffiffiffiffi m p .…”
Section: A Materials and Specimen Preparationmentioning
confidence: 99%
“…Estimation of motion and deformation by digital image correlation (DIC) has found increasing applications in mechanical testing of materials and structures [1][2][3][4][5][6][7][8]. While many DIC algorithms developed over the years have provided deformation measurements of acceptable accuracy and precision using high-quality digital image data, factors such as inherent image noise [9], subpixel interpolation approximation [10], and the mismatch between the actual deformation field of an image subset and the presumed deformation function for the subset [11][12][13] all tend to degrade the deformation parameter estimation.…”
Section: Introductionmentioning
confidence: 99%