| Fitting Algorithm of Microstructure Image of Carbon Black Reinforced Rubber Composites |
| Received:April 16, 2022 Revised:April 16, 2022 |
| DOI：10.12136/j.issn.1000-890X.2023.01.0068 |
| Key Words: rubber composite；carbon black reinforcing；carbon black aggregate；microstructure；image processing；fitting algorithm；contour skeleton algorithm；PSNR；SSIM |
| Author Name | Affiliation | E-mail | | HE Hong | Beijing University of Chemical Technology | hehong@mail.buct.edu.cn | | CHEN Zengyun | Beijing University of Chemical Technology | | | ZHANG Yaru | Beijing University of Chemical Technology | | | ZHANG Yishen | Beijing University of Chemical Technology | | | ZHANG Liqun | Beijing University of Chemical Technology | | | LI Fanzhu* | Beijing University of Chemical Technology | |
|
| Hits: 1438 |
| Download times: 848 |
| Abstract: |
| 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. |
|
View Full Text
View/Add Comment Download reader |
| Close |
