Gradation measurement of asphalt mixture by X-Ray CT images and digital image processing methods

Chao Xing, Huining Xu, Yiqiu Tan, Xueyan Liu, Changhong Zhou, Tom Scarpas

Research output: Contribution to journalArticleScientificpeer-review

10 Citations (Scopus)

Abstract

Gradation measurement is important for quality control of pavement construction. Computed tomography (CT) can capture the microstructure images of asphalt mixture. However, an accuracy digital image processing method should be developed. In this study, fuzzy network, multilevel threshold and morphological methods are utilized to reduce the noise, enhance the contrast and segment images. The 2D aggregate gradation obtained from the digital image segmentation procedure is transferred into 3D gradation by stereological method. The results show that fuzzy network can balance the noise reduction and contrast enhancement. The multilevel Otsu's threshold method can obtain the two thresholds automatically. The morphological processing and watershed transformation can fill the holes in the image and break the aggregate connections. By comparing the calculated gradation and the designed gradation, the image processing procedure proposed in this paper can be utilized to obtain the gradation information of AC, SMA and OGFC accurately and effectively.
Original languageEnglish
Pages (from-to)377-386
Number of pages10
JournalMeasurement: Journal of the International Measurement Confederation
Volume132
DOIs
Publication statusPublished - 2019

Keywords

  • Computed tomography
  • Digital image processing
  • Fuzzy network
  • Gradation

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