Application of Kendall's rank function for digital image correlation. (1st March 2019)

• Record Type: Journal Article
• Authors: Liu, Siqi; Tu, Peihan; Xu, Weichao; Xie, Shengli; Wu, Weizeng; Zhang, Yang; Zhou, Yanzhou
• Is Part Of: Measurement science & technology. Volume 30:Number 4(2019:Apr.)
• Publication Date: 2019-03-01
• Subjects: Kendall's rank correlation function -- salt-and-pepper noise -- nonlinear distortion of light intensity -- DIC; Physical measurements -- Periodicals; Scientific apparatus and instruments -- Periodicals; Equipment and Supplies -- Periodicals; Science -- instrumentation -- Periodicals; Technology -- instrumentation -- Periodicals; Mesures physiques -- Périodiques; Physical measurements; Scientific apparatus and instruments; Periodicals; 502.87
• DOI: 10.1088/1361-6501/aaf2e4
• Languages: English
• ISSNs: 0957-0233

Abstract

Abstract: Digital image correlation (DIC) is a widely used technique for measuring the surface deformation of solid materials and structures. A new criterion, called Kendall's rank correlation function (KRCF), has been applied to replace the traditional Pearson's product moment correlation function (PPMCF), which is a zero-mean normalized cross-correlation criterion in essence. By comparing the rank information of the reference and target subsets, the difference between the concordant and discordant pairs is larger and their correlation is higher. Simulations and experiments show that the performance of KRCF is better than PPMCF in an environment with: (1) salt-and-pepper noise; (2) monotone nonlinear light intensity distortion; (3) a fixed bright spot; and (4) cracks.