# Newly Designed Identification Scheme for Monitoring Ice Thickness on Power Transmission Lines
## 6 Conclusions  
This paper proposes a method of line icing identification for PTLI monitoring. In the initial stage, we integrate image restoration techniques with image filter enhancement to restore the image's color information. This combined approach effectively retains valuable information and preserves the original image quality, thereby mitigating noise introduced during the image acquisition. Subsequently, in the second stage, this paper introduced an enhanced multi-threshold algorithm to accurately separate background and target pixels. Through connected component labeling modification and mathematical morphology operations, we improve the image and find the region of interest (ROI) while eliminating the background regions. We apply the proposed method to measure ice thickness in the PTLI scene, and the average accuracy can be up to 90% compared with manual measurement. Based on the result of the evaluation matrix for validation of our proposed scheme, the accuracy value is 97.71%, the precision value is 96.24%, the recall value is 86.22%, and the specificity value is 99.48%. Our proposed scheme is reliable for PTLI images with complex backgrounds, images with poor illumination, and the position of the transmission line. Another advantage of this scheme is being able to distinguish between objects and backgrounds. Identification of the top and bottom lines has also been successfully conducted by marking a different color between the top and bottom lines to  
\begin{table}
\begin{tabular}{l l l l l} \hline  & **Location** & **1** & **2** & **3** \\ \cline{2-5} \multirow{3}{*}{**Experiment 1**} & Manual measurement (mm) & 88.80 & 81.50 & 84.1 \\  & Previous method (mm) [23; 24] & 119.4 & 92.1 & 94.5 \\  & Proposed method (mm) & 89.5 & 81.0 & 85.9 \\  & Absolute Error & 0.70 & 0.56 & 1.80 \\ \hline  & **Location** & **1** & **2** & **3** \\ \cline{2-5} \multirow{3}{*}{**Experiment 2**} & Manual measurement (mm) & 83.2 & 89.2 & 86.8 \\  & Previous method (mm) [23; 24] & 73.8 & 119.8 & 91.2 \\  & The proposed method (mm) & 73.2 & 87.5 & 85.3 \\  & Absolute Error & 1.0 & 1.7 & 0.5 \\ \hline  & **Location** & **1** & **2** & **3** \\ \cline{2-5} \multirow{3}{*}{**Experiment 3**} & Manual measurement (mm) & 90.2 & 87.8 & 80.06 \\  & Previous method (mm) [23; 24] & 120.8 & 118.4 & 90.46 \\ \cline{1-1}  & The proposed method (mm) & 89.7 & 87.1 & 79.1 \\ \cline{1-1}  & Absolute Error & 0.5 & 0.7 & 1.5 \\ \hline \end{tabular}
\end{table}
Table 5: The experimental result for ice thickness (mm).  
make it easier to measure the thickness of the ice. Therefore, this reliable scheme effectively resolves iced transmission line identification issues and significantly increases automation.  
Despite good recognition results, the transmission line recognition and extraction algorithm proposed in this paper still needs further research. For example, if the position of the object (the transmission line icing) in the image is visible from end to end, it will be challenging to recognize the upper and lower lines because, in this study, the image used only takes the smallest part of the transmission line icing into consideration. Additionally, the recall or sensitivity in this scheme is only 86%, so further improvement of image segmentation in transmission line icing images is needed. With the continuous development of UAV and multimedia technology, future detection of transmission lines will be more accurate and convenient. Therefore, this study provides insight for future research with video stream information using real scenes.  
The ideas and concepts were carried out in collaboration with all authors. [PERSON] and [PERSON] conceived and designed the experiments; [PERSON] and [PERSON] performed the experiments; [PERSON] and [PERSON] analyzed the data; [PERSON] and [PERSON] wrote the paper. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
The authors declare no conflict of interest.