Three phases segmentation from Ni/YSZ anode optical microscopy images using quantum-inspired mixture clustering model

Xiaowei Fu; Chengzhen Guo; Xin Xu; Xi Li

doi:10.1117/1.OE.57.7.073107

18 July 2018 Three phases segmentation from Ni/YSZ anode optical microscopy images using quantum-inspired mixture clustering model

Xiaowei Fu, Chengzhen Guo, Xin Xu, Xi Li

Author Affiliations +

Optical Engineering, Vol. 57, Issue 7, 073107 (July 2018). https://doi.org/10.1117/1.OE.57.7.073107

Abstract

Three-phase segmentation of solid oxide fuel cell (SOFC) anode image is essential for its microstructure quantitative analysis. A quantum-inspired mixture clustering model is developed for Ni/YSZ anode optical microscopy (OM) images. The proposed mixture clustering model focuses on combining Markov random field (MRF)-based fuzzy logic model with Gaussian mixture model (GMM). In the premise part of fuzzy if-then rules, the clique potential MRF function is defined by multiplication of both prior distributions and fuzzy membership functions with a quantum-inspired adaptive fuzzy degree, which takes prior statistics properties and spatial contextual information of SOFC anode OM image into consideration. In addition, GMM is introduced into the consequent part to design a negative log-prior function as the pixel distance metric. The proposed method has been compared to other state-of-the-art segmentation algorithms on both simulated images and real SOFC anode OM images. The experimental results demonstrate that the proposed method is able to achieve a higher segmentation accuracy with a faster convergence speed, which lays firm foundation for microstructural parameters extraction from SOFC electrodes image datasets.

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Xiaowei Fu, Chengzhen Guo, Xin Xu, and Xi Li "Three phases segmentation from Ni/YSZ anode optical microscopy images using quantum-inspired mixture clustering model," Optical Engineering 57(7), 073107 (18 July 2018). https://doi.org/10.1117/1.OE.57.7.073107

Received: 26 December 2017; Accepted: 25 June 2018; Published: 18 July 2018

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