A Novel Ni/YSZ Anode Image Segmentation Method for Solid Oxide Fuel Cell Electrodes Microstructure

For the three-phase identification of solid oxide cuel cell (SOFC) electrode, this paper presents a novel segmentation method based on gaussian mixture model (GMM) for YSZ/Ni anode optical microscopy (OM) images. A coarseness-entropy adaptive factor is defined to incorporate the spatial information based on markov random field (MRF) into GMM. Furthermore, the proposed method can obtain the trade-off between robustness to noise and effectiveness of preserving the details. Experimental results show that the proposed method outperforms the compared method on three-phase microstructure identification. It can provide reliable foundation for the quantification of SOFC microstructure parameters.