## 2 Materials and Methods
### Data Preprocessing  
In the pre-processing step, we focused on developing an image-processing technique that can delineate the characteristics of RNFL. RNFL is located around blood vessels and also close to the OD. As illustrated in Figure 1, the occurrence of RNFL was not clear, as there were blood vessels and OD in the way. Hence, we analyzed the RGB color space by separating every color channel and took a closer look into each of them. Finally, we found that the green channel of the RGB color space delineated the RNFL clearly. However, OD and blood vessels might still become an obstacle in the analysis process. Hence, in this step, we performed an OD and blood vessel removal scheme. The complete steps of the scheme are illustrated in Figure 3. As illustrated in Figure 3, the first step that is conducted in our experiment is OD and blood vessel removal. This process is carried out by conducting OD and blood vessel segmentation. The first important step before beginning the segmentation step is to locate the optic disc or optic nerve. This step is necessary to eliminate any peripheral area and merely focus on the optic nerve area. \begin{table}
\begin{tabular}{c c} \hline \hline
**Scope of Research** & **Researcher** \\ \hline Optic disc and optic cup localization and segmentation & [26; 27; 28; 29; 30; 31; 32; 33; 34; 35; 36] \\ \hline Classification of glaucoma disease & [20; 37; 38; 39; 40; 41] \\ \hline Glaucoma detection & [42; 43; 44; 45; 46] \\ \hline CDR estimation & [47] \\ \hline Explainable or interpretable AI for glaucoma detection & [48; 49] \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Recent studies in using ORIGA-light dataset. Figure 3: The scheme of preprocessing process. In addition to Figure 3, Figure 4 illustrates the proposed technique of optic disc localization. Optic disc localization is conducted by first creating frames for every side of the input image. The frame width is 600 pixels from the peripheral to the center of the image, as shown in Figure 5b. This frame is useful to avoid the bright fringes around the retinal image. The bright fringe shown in Figure 5a is an area with a resemblance to the optic disc in terms of intensity value. A large area of the fringe can be mistaken as the optic disc, thereby leading to lower accuracy of localization. Hence, the RGB images need to subsequently be converted into a gray image by only taking the green channel. Then, this gray image can proceed to the next step. Since the dataset used in this experiment contained RGB images, we need to remove two channels and retain the other one. Because OC and OD may be seen in the green channel with more clarity than in the other two channels, the green channel is kept while the other two channels are discarded. Figure 6 illustrates the differences between each channel. Figure 6a illustrates an image of a red channel, Figure 6b illustrates an image of a green channel, and Figure 6c illustrates an image of a blue channel. According to these pictures, we can see that the image of the green channel appears clearer than other channels. Figure 4: The algorithm of optic disc localization. Figure 5: The fringe (**a**) is shown by the white arrows. To eliminate the fringe, a frame (**b**) is added on the side of the image. To yield a coherent RoI (region of interest) of the optic disc, searching for the center point is necessary. The search is conducted automatically by utilizing every column of the gray image's matrix to find the highest pixel value. In Algorithm 1, _I, queue, Total_Column, val, ldx_ represent the gray image, array lists containing the index of _val_, the number of columns of the gray image, the maximum intensity value of the current column, and the index of the maximum intensity value, respectively. ```
1:input: given \(I\)
2:given queue
3:for\(n=1\) to Total_Columndo
4:val = maximum value of \(I_{n}\)
5:ldx = index of val
6:If\(\text{val}\geq 10\)then
7:store ldx to queue
8:endif
9:endfor
```  
**Algorithm 1**The search for the highest pixel value from every column of the image.