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The input test image shown below has a multi directional crack and high coarseness. The 100 by 100 patch of pavement with no crack and the fused crack on the patch is shown in figure 6. Fig. 6. Original and synthetic cracks

Figure 6 The input test image shown below has a multi directional crack and high coarseness. The 100 by 100 patch of pavement with no crack and the fused crack on the patch is shown in figure 6. Fig. 6. Original and synthetic cracks

Related Figures (12)

Fig. 1. Gabor filter at 0 degree orientation P(x, y) = E°@.y) = oy) + jg vy) (8) A Gabor filter of wavelength of 20, variance = 4, phase offset = 0 is shown in Fig. 2. And the frequency response of the Gabor filter is illustrated in Fig. 2.
Fig. 1. Gabor filter at 0 degree orientation P(x, y) = E°@.y) = oy) + jg vy) (8) A Gabor filter of wavelength of 20, variance = 4, phase offset = 0 is shown in Fig. 2. And the frequency response of the Gabor filter is illustrated in Fig. 2.
Fig. 2. Frequency response of filter in Fig. 1
Fig. 2. Frequency response of filter in Fig. 1
Fig. 3. Structure of Genetic Algorithm The SSIM metric of an image is calculated on a variety of windows. To evaluate between two windows x and y of size V x N is:
Fig. 3. Structure of Genetic Algorithm The SSIM metric of an image is calculated on a variety of windows. To evaluate between two windows x and y of size V x N is:
Fig. 5. The process of creating the ground truth The synthetic crack is arbitrary, thin as compare to original cracks and most importantly is stretched almost every direction. All these characteristics make this crack appropriate for fusion in real texture of road. As mentioned earlier that intensity values of cracks are low as compare to the rest of pavement texture but the texture is not uniform and changes continuously, the intensity must be less than the average intensity of the image. The flow diagram for simulated ground truth is shown in figure 5.
Fig. 5. The process of creating the ground truth The synthetic crack is arbitrary, thin as compare to original cracks and most importantly is stretched almost every direction. All these characteristics make this crack appropriate for fusion in real texture of road. As mentioned earlier that intensity values of cracks are low as compare to the rest of pavement texture but the texture is not uniform and changes continuously, the intensity must be less than the average intensity of the image. The flow diagram for simulated ground truth is shown in figure 5.
To increase the robustness of the optimization of Gabor parameters, the technique of simulated ground truth is used. This ground truth is simulated from within the texture of test image after selecting a 100 by 100 patch containing flexible pavement texture but no crack. There are relatively few low intensity pixels as compare to mean of whole patch. Low intensity pixels contain the crack present in image that is why it is avoided. This 100 by 100 patch is fused with another patch of same size which contains a synthetically created multi oriented crack as shown in figure 4. Fig. 4. Synthetic crack
To increase the robustness of the optimization of Gabor parameters, the technique of simulated ground truth is used. This ground truth is simulated from within the texture of test image after selecting a 100 by 100 patch containing flexible pavement texture but no crack. There are relatively few low intensity pixels as compare to mean of whole patch. Low intensity pixels contain the crack present in image that is why it is avoided. This 100 by 100 patch is fused with another patch of same size which contains a synthetically created multi oriented crack as shown in figure 4. Fig. 4. Synthetic crack
The 100 by 100 sized simulated ground truth is shown below in figure 7. Fig. 7. Simulated Ground Truth
The 100 by 100 sized simulated ground truth is shown below in figure 7. Fig. 7. Simulated Ground Truth
The output of the system is computed by the precision and recall of the manually selected and optimized Gabor filter not by the values of the variance and wavelength of the optimized Gabor filter. The graph below in figure 12 shows the precision of five pavement crack images
The output of the system is computed by the precision and recall of the manually selected and optimized Gabor filter not by the values of the variance and wavelength of the optimized Gabor filter. The graph below in figure 12 shows the precision of five pavement crack images
Fig. 9. Left: manually selected Gabor filter extracted crack, Right: crack extracted by optimized Gabor filter Fig. 8. b. Crack Detection algorithm (Flow chart)
Fig. 9. Left: manually selected Gabor filter extracted crack, Right: crack extracted by optimized Gabor filter Fig. 8. b. Crack Detection algorithm (Flow chart)
Fig. 10. Left: manually selected Gabor filter extracted crack, Right: crack extracted by optimized Gabor filter
Fig. 10. Left: manually selected Gabor filter extracted crack, Right: crack extracted by optimized Gabor filter
Fig. 12. Comparison between manual and Optimized Precision Fig. 11. Comparison between manual and Optimized Precision
Fig. 12. Comparison between manual and Optimized Precision Fig. 11. Comparison between manual and Optimized Precision
Related topics:
Computer ScienceArtificial IntelligenceGabor filtersAutomated DetectionGabor FilterParameter Selection
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