Applications of digital-image-correlation techniques to experimental mechanics

Gold, enigmatically represented by the target-like design of its ancient alchemical symbol, has been considered a mystical material of great value for centuries. Nanoscale particles of gold now command a great deal of attention for biomedical applications. Depending on their size, shape, degree of aggregation, and local environment, gold nanoparticles can appear red, blue, or other colors. These visible colors reflect the underlying coherent oscillations of conduction-band electrons (“plasmons”) upon irradiation with light of appropriate wavelengths. These plasmons underlie the intense absorption and elastic scattering of light, which in turn forms the basis for many biological sensing and imaging applications of gold nanoparticles. The brilliant elastic light-scattering properties of gold nanoparticles are sufficient to detect individual nanoparticles in a visible light microscope with ∼102 nm spatial resolution. Despite the great excitement about the potential uses of gold nanoparticles for medical diag...

Gold nanoparticles in biology: beyond toxicity to cellular imaging

Two-dimensional image motion is the projection of the three-dimensional motion of objects, relative to a visual sensor, onto its image plane. Sequences of time-orderedimages allow the estimation of projected two-dimensional image motion as either instantaneous image velocities or discrete image displacements. These are usually called the optical flow field or the image velocity field. Provided that optical flow is a reliable approximation to two-dimensional image motion, it may then be used to recover the three-dimensional motion of the visual sensor (to within a scale factor) and the three-dimensional surface structure (shape or relative depth) through assumptions concerning the structure of the optical flow field, the three-dimensional environment, and the motion of the sensor. Optical flow may also be used to perform motion detection, object segmentation, time-to-collision and focus of expansion calculations, motion compensated encoding, and stereo disparity measurement. We investigate the computation of optical flow in this survey: widely known methods for estimating optical flow are classified and examined by scrutinizing the hypothesis and assumptions they use. The survey concludes with a discussion of current research issues.

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The computation of optical flow

Digital image correlation is finding wider use in the field of mechanics. One area of weakness in the current technique is the lack of available displacement gradient terms. This technique, based on a coarse-fine search method, is capable of calculating the gradients. However the speed at which it does so has prevented widespread use. Presented in this paper is the development and limited experimental verification of a method which can determine displacements and gradients using the Newton-Raphson method of partial corrections. It will be shown that this method is accurate in determining displacements and certain gradients, while using significantly less CPU time than the current coarse-fine search method.

Digital image correlation using Newton-Raphson method of partial differential correction

The development of the method of particle image velocimetry (PIV) is traced by describing some of the milestones that have enabled new and/or better measurements to be made. The current status of PIV is summarized, and some goals for future advances are addressed.

WJ Wolters

Papers

Determination of displacements using an improved digital correlation method