摘要
针对固体氧化物燃料电池(SOFC)的电极孔隙率评估问题,提出了一种基于区域生长的图像分割改进方法来标识出电子显微镜下电极图像中的孔隙。该方法首先利用Otsu阈值法获取原图像的二值图像并标记连通区域,然后在每一个连通区域选取一个灰度值最小的像素点作为种子点进行区域生长,最后根据区域生长后的结果图像计算SOFC孔隙率。实验结果表明该方法可以有效地计算SOFC电极孔隙率用于分析SOFC的性能。
To tackle electrode porosity evaluation for solid oxide fuel cell（SOFC）, an image segmentation approach was proposed to exploit region growing for identifying the pores in scanning electron microscopy（SEM） electrode images for the first time. Firstly, the proposed approach extracted the connected regions of the binary image using conventional OTSU thresholding. Then, the pixels with the minimum gray value in each connected region were selected as seed points for region growing. Finally, the SOFC porosity was calculated using the result image obtained from the region growing. Experiment shows that the proposed method is effective to calculate the SOFC electrode porosity for its performance analysis.
出处
《电源技术》
CAS
CSCD
北大核心
2016年第3期572-574,624,共4页
Chinese Journal of Power Sources
基金
国家自然科学基金项目(61201423
61573162)
智能信息处理与实时工业系统湖北省重点实验室开发基金子项目(znss2013B016)
武汉科技大学研究生院教研项目(Yjp1311
Yjg201309)
2015年湖北省科技支撑计划项目(2015BCE059)
