Automatic grain boundary detection and grain size analysis using polarization micrographs or orientation images

A simple procedure for creating grain boundary maps from petrographic thin sections, termed the Lazy Grain Boundary (LGB) method, has been devised. It is based on a set of macro commands programmed for NIH Image, a public domain image processing software. The grain boundary detection is based on gradient filtering. The procedure makes use of multiple input images: sets of regular polarized micrographs or—where possible—orientation/misorientation images. On each image of a given input set, only the most significant grain boundaries are detected and by combining those, a single grain boundary map is obtained. Image models and criteria for grain boundary identification are discussed briefly. The principal aim of the LGB method is to facilitate the production of large grain boundary maps (containing several thousand cross-sectional areas) to provide statistically valid samples for grain size analysis. ion of Black Hills quartzite was used to test the LGB method. Five different input sets were prepared and used for automatic LGB analysis. One set was additionally used for an interactive analysis and for a manual tracing. From all seven grain boundary maps, the 2- and 3-D grain size distributions were calculated. The results are compared and the different image sets and procedures are rated for precision, over- and undersegmentation and speed of preparation.