Abstract
This study is based on the processing of computed microtomography images of rock samples. In this study, a finite automation is constructed using the grey value, red-green-blue (RGB) value and Euler number of polarized images of carbonate rocks from the Jingfengqiao–Baidiao area. The finite automaton is used to perform black and white binary processing of the polarized images of the carbonate rocks. The porosity of the carbonate rock is calculated based on the black and white binarization processing results of the polarized images of the carbonate rocks. The obtained porosity is compared with the carbonate porosity obtained by use of the traditional carbonate research method. When the two porosities are close, the image processing threshold of the finite automata is considered to be credible. Based on the finite automata established using the image processing threshold, the black and white binary images of the polarized images of the carbonate rocks are used to establish a rock pore image using ImageJ2X. The polarized images of the carbonate rocks are classified according to their RGB values using the finite automata for the porosity classification, and the obtained images are used as textures to paste onto a cube to construct a three-dimensional data model of the carbonate rocks. This study also uses 16S rDNA analysis to verify the formation mechanism of the carbonate pores in the Jingfengqiao–Baidiao area. The results of the 16S rDNA analysis show that the pores in the carbonate rocks in the Jingfengqiao–Baidiao area are closely related to microorganisms, represented by denitrifying bacteria.
Highlights
Studying the porosity of carbonate rocks is important to karst research
(iii) The method of using finite automata to study the pores in the polarized images of the carbonate rocks from the Jingfengqiao area was mainly established using the image processing threshold, which is mainly composed of the grey value, RGB value, or Euler number
(v) In the Jingfengqiao area, if the Euler number is used to determine the image processing threshold 16 of the finite automata, the final Euler number must be converted to a grey value or RGB value, which is used as the image processing threshold of the finite automata
Summary
Studying the porosity of carbonate rocks is important to karst research. It is necessary to use computer image royalsocietypublishing.org/journal/rsos R. Analysis to study the porosity of carbonate rocks. The traditional carbonate research method 2 (TCRM) was used to verify the accuracy of the carbonate porosity results obtained using computer image analysis. The expansion of carbonate pores is sometimes related to the microorganisms in the karst water. To determine whether or not microorganisms affected the karst process in the karst water system, researchers only need to perform a 16S rDNA test
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