【摘要】 使用一种基于Python语言的图像处理技术，对泡沫金属孔隙的横截面积、孔穴棱边周长、费雷特直径、孔隙形态等参数进行精确表征，实现对泡沫金属图像的相对密度批量化计算及输出。检测结果精确到了0.001,对单个孔隙进行特征表征只需0.008 5 s,较传统方法缩短了82.354 5 s,对146个孔隙进行特征表征只需1.241 s。更多还原

【Abstract】 An image processing technology based on Python language was applied to accurately characterize parameters such as the cross-sectional area, hole edge circumference, Ferret diameter and pore morphology of metal foam pores, so as to achieve mass calculation and output of the relative density of metal foam images. The detection result is accurate to 0.001. It takes only 0.008 5 s to characterize a single pore, which increases the detection efficiency by 82.354 5 s compared with the traditional method, and takes only 1.241 s to characterize 146 pores.更多还原