Observer-dependent variability of the thresholding step in the quantitative analysis of soil images and X-ray microtomography data

By Philippe C. Baveye, Magdeline Laba, Wilfred Otten, Liesbeth Bouckaert, P. D. Sterpaio, R. R. Goswami, Dmitry V Grinev, Alasdair N. Houston, Yaoping Hu, Jianli Liu and 7 more. 2010

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Image processing of multiphase images obtained via X‐ray microtomography: A review (2014, methodology): “A notorious example is image segmentation of a gray value image into objects and background [Sezgin and Sankur, 2004; Iassonov et al., 2009; Baveye et al., 2010].”
Using X-ray computed tomography in pore structure characterization for a Berea sandstone: Resolution effect (2012, methodology): “Determining the boundary grayscale threshold is critical for the final results on the pore geometry, and can be carried out by either thresholding algorithms or manually; as indicated in Baveye et al. (2010), in which three CT images were analyzed by 13 experts using different routines.”
New Local Thresholding Method for Soil Images by Minimizing Grayscale Intra‐Class Variance (2013, background): “However, various tests on soil images show that this threshold produces a clear overestimation of the pore space (Baveye et al., 2010; Wang et al., 2011).”