## 4 Conclusions  
Our findings have important implications for the construction industry and sustainable development. By leveraging Micro-CT imaging technology, we successfully obtained detailed images of concrete test cores containing various proportions of gravel, EVA, and natural fibers. These images were then meticulously segmented to differentiate between the components, with the cementitious matrix serving as the background against which pores, EVA fragments, and fibers were identified as distinct objects. This segmentation process laid the foundation for the creation of a Takagi-Sugeno-Kang type fuzzy inference system, which, in turn, facilitated the classification of objects within the foreground as pores, EVA, or fibers. The application of this kind of inference is unprecedented in fiber lightweight concrete characterization and can be applied in other material characterizations using DIP.  
Figure 11: Visualization of the linear correlation between the reference values and values estimated for porosity and EVA and gravel contents, indicating the values of the metrics used.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Component** & **a (\%/\%)** & \(r_{xy}\) & **nRMSE** & \(\mathbf{Q}\) \\ \hline GRAVEL & 0.958 & 0.672 & 0.147 & 0.873 \\ EVA & 1.018 & 0.853 & 0.253 & 0.913 \\ PORE & 1.022 & 0.910 & 0.211 & 0.925 \\ \hline MEAN & 0.999 & 0.812 & 0.204 & 0.904 \\ \hline \hline \end{tabular}
\end{table}
Table 8: Metrics for evaluating the linear correlation between estimated and reference values of porosity and EVA and gravel contents.  
The tool we have developed not only provides precise estimates of the percentages of gravel and EVA within a concrete core but also offers valuable insights into the porosity of the material. This breakthrough enables a deeper understanding of the internal structure and performance potential of these alternative concrete mixtures.  
In conclusion, our study represents a notable milestone in the characterization of composite concrete, lending crucial support to the adoption of sustainable construction materials. Through the introduction of an innovative methodology for assessing concrete blends incorporating EVA and natural fibers, we equip the industry with the tools to manufacture structures that are not only lighter, more durable, and cost-efficient but also environmentally conscious. However, further research is imperative to enhance the precision and sensitivity required for accurately quantifying low amounts of fibers in this particular class of concrete formulations.  
Conceptualization, S.M.I. and D.S.D.; methodology, M.A.S.S., S.M.I. and D.F.; software, M.A.S.S.; validation, M.A.S.S. and I.B.R.O.; formal analysis, S.M.I. and P.E.A.; writing--original draft preparation, M.A.S.S. and S.M.I.; writing--review and editing, I.B.R.O. and D.F.; supervision, S.M.I. and P.E.A.; funding acquisition, D.S.D. and S.M.I. All authors have read and agreed to the published version of the manuscript.  
This research was partially funding by the Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior, Brazil (Finance Code 001) and Research Support Program of the Universidade Estadual de Santa Cruz.  
Not applicable  
Data Availability StatementData available on request from the corresponding author due to privacy restrictions.  
The authors of the study would like to thank the Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior, Brazil, for the partial financial support to carry out this study.  
The authors declare that there are no financial or personal conflict directly or indirectly related to this work.  
The following abbreviations are used in this manuscript:  
Micro-CT X-ray Computed Microtomography  
TSK Takagi-Sugeno-Kang  
DIP Digital Image Processing