A FUZZY-LOGIC APPROACH TO EDGE-DETECTION IN HREM IMAGES OF III-V CRYSTALS

Edge detection algorithms have been developed to partition an image fi eld into subfields representing regions with different properties. Edg es are defined by relatively notable and distinguishable image changes . Among advanced theories, fuzzy logic (FL) is highly suited to detect such edges. High-resolution electron micrographs (HREM) of crystallin e specimens reveal the nature of crystals. For studying interdiffusion phenomena in layered structures of III-V compounds, image variations, described by the term similarity, are interpreted. Contrary to natura l images, a periodic array of subunits (crystal cells) dominates the i mage patterns in HREM applications. The crystallographic cells are rep resented by values of similarity, related to known templates of a III- V compounds by a difference measure of similarity. The idea of this fu zzy edge detection algorithm is to analyze the transition taking place between the two neighboring sides of the edge. The limited number of cells requires fitted masks of neighboring cells, and also serves as i nput to the set of dedicated fuzzy rules. Applying two triangular memb ership functions, the location of the most significant composition ste ps can be determined. After analyzing simulated HREM patterns, the fuz zy logic development tool has been employed to obtain the edges on exp erimental micrographs of MBE-grown Al/GaAs.