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As such, some techniques that can automatically predict shell content only from stained thin section image are proposed.
Moreover, within each thin section image, the main lithology predicted in accordance with the calculated shell content is consistent with that deduced from the expected shell content.
The texture identifier model extracts thirteen features to recognize texture type and the porosity analyzer determines percentage of each type of porosity based on eleven features extracting from the thin section image.
The processing procedures of those techniques include four steps: binarizing color thin section image; detecting edges of objects; using a special technique to extract shell areas; finally adjusting appearances of those extracted shells by dilating and eroding.
Fig. 3 Thin section image of large plagioclase crystals.
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Our algorithm uses 12 color features that are extracted from thin section images.
In the present research, the capabilities of intelligent systems are employed to develop two algorithms for identification of textural and pore space characteristics of carbonate rocks from thin section images.
Soils with porosities of > 50 μm and 0.5 50 μm were directly quantified by analyzing thin section images prepared from undisturbed soil samples, collected in situ in Kubiena boxes in 2008 and 2010.
The small errors and exact judgments of the lithology manifest that the proposed techniques are capable to provide the reliable shell content data, and compared to the conventional observation and analysis methods they are cost-efficient when dealing with a large amount of thin section images.
Using the analytical functions in ImageJ, the connected porosity was calculated on all binary thin section images as a percentage of the total area of the binary image that was black (void space).
A laminated and variegated granular morphology, displaying alternating electron-dense and pervious layers resembling "bull's eyes," could be more clearly seen with NB "strains" that had been maintained through multiple serial passages in the presence of excess serum (5 10% FBS), as illustrated by thin section images of "nanons" shown in the bottom row of Figure 5 (Q T).
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