Analysis of Defects in Microscopic Images of Hetero Epitaxial Growth Technique Using Fuzzy K Means Clustering Algorithm

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The semiconductor material InP plays a key role in optoelectronic devices, high-speed devices, and fiber optic communications systems. The major problems with these materials are the high lattice mismatch and variance in thermal expansion coefficient between InP and Si. This mismatch produces high dislocation density at the interface and the propagation of the threading dislocations away from the interface into the device layer is a major concern in optoelectronic applications. Image processing algorithms play a pivotal role in the medical field, archaeology, and remote sensing. This work proposes an image processing method to analyze the SEM images of the InP heteroepitaxy layer to determine the etch pits to confirm whether the substrate is suitable for optoelectronic applications. In this work, a variant of an anisotropic diffusion filter for noise reduction on SEM images and Fuzzy C means clustering method for image segmentation was employed for analysis.