# Mineral Identification Based on Deep Learning Using Image Luminance Equalization
## 2 The Proposed Method
### A New Algorithm Based on HELaplace
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Studies** & **Accuracy (\%)** & **Number of Identified Minerals** & **Image Type** \\ \hline
[10] & 89 & 5 & Microscopic \\
[11] & 95 & 2 & Microscopic \\
[12] & 90 & 9 & Microscopic \\
[13] & 90.9 & 4 & Microscopic \\
[14] & 90 & 4 & Microscopic \\
[15] & 95.4 & 23 & Microscopic \\
[34] & \(\backslash\) & 23 & CT \\
[35] & 94.2 & 5 & Raman spectra \\
[16] & 90.6 & 36 & Photo and hardness \\
[17] & 86 & 16 & Photo \\
[18] & 90 & 7 & Photo \\ Our method & 95.6 & 50 & Photo \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Comparison of deep learning-based and image-based mineral identification works. nition part, we used YOLOv5 to further improve the identification accuracy. During model selection, we used the optimized YOLOv5 to further improve the identification accuracy. In the future, more features will be introduced, such as combining the density and transparency of minerals with photos to further improve the accuracy of mineral identification. However, the identification method mentioned in this paper has some limitations: when the input picture is a mineral other than fifty minerals, the closest one among fifty minerals will be given. In the future, we will collect more mineral data to address this issue. Conceptualization, T.L. ; Data curation, J.Z. and H.L. ; Funding acquisition, T.L. ; Methodology, J.Z. ; Supervision, T.L. ; Visualization, J.Z., Q.G. and H.L. ; Writing--original draft, J.Z. and Q.G. ; Writing--review and editing, T.L. All authors have read and agreed to the published version of the manuscript. This work was supported by National Natural Science Foundation of China under Grants No. 62002332, 62072443. Data Availability Statement: Data sharing is not applicable. Thanks are given to [PERSON], [PERSON], and [PERSON] for their help in collecting the mineral samples. The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results. ## References

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