2017
DOI: 10.1177/0144598717690090
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Multi-component segmentation of X-ray computed tomography (CT) image using multi-Otsu thresholding algorithm and scanning electron microscopy

Abstract: X-ray computed tomography is an efficient method for quantitatively estimating the characteristics and heterogeneity of shales in three dimensions. A threshold is commonly used to separate pore-fractures from the background image. However, few studies have focused on the multicomponent segmentation of computed tomography images. To obtain the distribution characteristics of different components in three dimensions, a segmentation method was proposed that combines a multi-Otsu thresholding algorithm with scanni… Show more

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Cited by 30 publications
(9 citation statements)
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“…b) Initialize the entropy of gray-level histogram using (8), where 𝑎 and 𝑏 are the minima and maximum gray-level intensity.…”
Section: Minimum Cross-entropy Methodsmentioning
confidence: 99%
“…b) Initialize the entropy of gray-level histogram using (8), where 𝑎 and 𝑏 are the minima and maximum gray-level intensity.…”
Section: Minimum Cross-entropy Methodsmentioning
confidence: 99%
“…Pores were segmented and analyzed automatically using ImageJ software, which initially transformed BSE images into an eight-bit bitmap using the tape function. Subsequently, BSE images were converted to pore binary images based on the threshold calculated by the Multi-Otsu thresholding algorithm (Zhang et al., 2017c). The representative elementary area (REA) was determined using the box-counting method on the pore binary images.…”
Section: Methodsmentioning
confidence: 99%
“…Otsu’s method was used to obtain the threshold for the automatic segmentation of the CT data 20 , 21 . This algorithm assumes that the image consists of pixels following a bi-modal histogram (foreground and background pixels), and it then calculates the optimum threshold separating the 2 classes so that their intra-class variance is minimal 22 .…”
Section: Methodsmentioning
confidence: 99%