橡胶复合材料中炭黑微观结构图像的拟合算法

Carbon black aggregates were considered to be composed of multiple circular primary particles，and the morphology of carbon black aggregates in rubber composites was analyzed by image fitting. Based on the microstructure image of carbon black reinforced rubber composites，three fitting algorithms，contour skeleton algorithm，maximum inscribed circle algorithm and K-means clustering algorithm to deal with carbon black aggregate morphology were studied based on using image segmentation and threshold iteration and other methods to handle image background defects. The image fitting effects were evaluated by two indicators of peak signal-to-noise ratio（PSNR）and structural similarity（SSIM）. The results showed that the contour skeleton algorithm had the best effect in fitting the morphology of carbon black aggregates，and it was more suitable for describing the morphology of carbon black aggregates in the microstructure reconstruction of carbon black reinforced rubber composites.