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... this study, the fastest detection method, YOLOv5, is used; the inference flow of the YOLO system is shown below. The network structure of YOLOv5 used in this study is shown in Figure 4, and is roughly divided into three parts: Backbone, Neck, and Head. Backbone creates feature maps for each image through convolutional operations. ...
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... three primary colors of light are red, green, and blue, and various colors can be created from these three colors. As shown in Figure 4, mixing red and cyan produces a whitish color. In this case, the image before corrosion is converted to a red scale without the green and blue information, and the image after corrosion is converted to a cyan scale without the red information. ...
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... other words, by adding both images together, changes before and after corrosion can be indicated by colors such as white, black, red, and cyan. As a specific example, as shown in the first line of Figure 4, the RGB values before and after corrosion progress are both black (0, 0, 0), so the color of the areas with no change before and after corrosion progress is close to black (0, 0, 0) in the additive color mixture result. In addition, the area where the bridge was stained in the previous year and the stain disappeared this year is cyan (0,255,255), as shown in the second line from the top in Figure 4. Similarly, areas where there was no corrosion but corrosion has progressed are closer to red (255,0,0), as shown in the third line from the top in Figure 4. Finally, if there is no change before and after corrosion, as in the case of black, the color is closer to white (255,255,255) in the result of additive mixing, as in the fourth line from the top of Figure 4. ...
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... a specific example, as shown in the first line of Figure 4, the RGB values before and after corrosion progress are both black (0, 0, 0), so the color of the areas with no change before and after corrosion progress is close to black (0, 0, 0) in the additive color mixture result. In addition, the area where the bridge was stained in the previous year and the stain disappeared this year is cyan (0,255,255), as shown in the second line from the top in Figure 4. Similarly, areas where there was no corrosion but corrosion has progressed are closer to red (255,0,0), as shown in the third line from the top in Figure 4. Finally, if there is no change before and after corrosion, as in the case of black, the color is closer to white (255,255,255) in the result of additive mixing, as in the fourth line from the top of Figure 4. ...
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... a specific example, as shown in the first line of Figure 4, the RGB values before and after corrosion progress are both black (0, 0, 0), so the color of the areas with no change before and after corrosion progress is close to black (0, 0, 0) in the additive color mixture result. In addition, the area where the bridge was stained in the previous year and the stain disappeared this year is cyan (0,255,255), as shown in the second line from the top in Figure 4. Similarly, areas where there was no corrosion but corrosion has progressed are closer to red (255,0,0), as shown in the third line from the top in Figure 4. Finally, if there is no change before and after corrosion, as in the case of black, the color is closer to white (255,255,255) in the result of additive mixing, as in the fourth line from the top of Figure 4. ...
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... a specific example, as shown in the first line of Figure 4, the RGB values before and after corrosion progress are both black (0, 0, 0), so the color of the areas with no change before and after corrosion progress is close to black (0, 0, 0) in the additive color mixture result. In addition, the area where the bridge was stained in the previous year and the stain disappeared this year is cyan (0,255,255), as shown in the second line from the top in Figure 4. Similarly, areas where there was no corrosion but corrosion has progressed are closer to red (255,0,0), as shown in the third line from the top in Figure 4. Finally, if there is no change before and after corrosion, as in the case of black, the color is closer to white (255,255,255) in the result of additive mixing, as in the fourth line from the top of Figure 4. In other words, areas that remain unchanged before and after the corrosion process return to their original color, while areas that have changed are displayed in cyan or red. ...
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... other words, areas that remain unchanged before and after the corrosion process return to their original color, while areas that have changed are displayed in cyan or red. Based on the above, as shown in the lower part of Figure 4, the additive mixture of color method can be used to identify only the areas where corrosion has progressed. However, it is assumed that the angle of view is the same for both images. ...
