Three‐dimensional reconstruction of fracture surfaces: Area matching algorithms for automatic parallax measurements

Abstract

Summary: This paper describes two solutions for systematic measurement of surface elevation that can be used for both profile and surface reconstructions for quantitative fractography case studies. The first one is developed under Khoros graphical interface environment. It consists of an adaption of the almost classical area matching algorithm, that is based on cross-correlation operations, to the wellknown method of parallax measurements from stereo pairs. A normalization function was created to avoid false crosscorrelation peaks, driving to the true window best matching solution at each region analyzed on both stereo projections. Some limitations to the use of scanning electron microscopy and the types of surface patterns are also discussed. The second algorithm is based on a spatial correlation function. This solution is implemented under the NIH Image macro programming, combining a good representation for low contrast regions and many improvements on overall user interface and performance. Its advantages and limitations are also presented.

Analysis of surface growth in shoot apices

“…A simple way to record the position of corresponding vertices on the reference and tilted images is to manually select the location from direct comparison. This approach is not only tedious, it also leads to unsatisfactory surface reconstructions (see also Hein et al ., 1999). The quality of the reconstruction is greatly improved if an area matching protocol is used to find corresponding vertex locations on the reference and tilted images.…”

“…A computational approach, such as area matching, is the most effective way to minimise the noise associated with positioning the same vertex on different images and, in this way, reduce the need for large tilts. For area matching to be effective, the image contrast must be optimised since matching formulae fail in areas of low contrast (Hein et al ., 1999). The quality of the reconstruction therefore depends on optimization of the magnification, the tilt angle, and image contrast during microscopy.…”

“…We developed an area matching protocol to find corresponding vertices on the tilted images (see also Hein et al ., 1999). For each vertex on the reference image, we searched a small region around the putative vertex location on the tilted meristem image.…”

Three‐dimensional representation of curved nanowires

“…There is a long list of experiments performed with the aim of realizing stereo‐vision by electron microscopy (Boyde, 1973; Thong & Breton, 1992; Hein et al ., 1999). All of these experiments involve using a series of micrographs obtained at different angles of incidence of the primary electron beam.…”

Quantitative fractography by digital image processing: NIH Image macro tools for stereo pair analysis and 3‐D reconstruction

“…The second group of routines is dedicated to elevation map computing, and consists of three macro programs. All of these programs consist of a matching algorithm based on spatial correlation of windows extracted from both images of the stereo pair, as described by the author in a recent paper (Hein et al ., 1999a). A reference window for each tested ( x , y ) position is extracted from the right image and it is successively compared to a sequence of scanning windows extracted from the stereo pair left projection.…”