# Algorithm Development for the Non-Destructive Testing of Structural Damage
## 5 Results and Discussion
### Evaluating Results for the Proposed SCM Algorithms
Figure 14: The total process of target segmentation of sample using Fourier transform and Gaussian followed by Multi-thresholding and erosion, with (1) single-, (2) two-fold, and (3) three-fold multiplications, (**a**) Fourier transforms, (**b**) inverted Fourier transforms (magnitude), (**c**) inverted Fourier transforms (phase), and (**d**) segmented results. Figure 15: Images of the sample, showing the total process of target segmentation, using fuzzy c-mean clustering, followed by multi-thresholding and erosion, (**a**) original image, (**b**) fuzzy c-mean clustering, (**c**) erosion by structuring element object 10, and (**d**) erosion by structuring element object 15. Also, this section presents the surface plots for the magnitude and phase of reconstructed images as a further comparison of Algorithms 1 and 2. Figure 16a shows the surface plot for the wavelet transform basis and Fourier transform (Algorithm 1). The plots in the first row of Figure 16a demonstrate the magnitude and phase of the 2D data, containing random phases. The plots in the second row of Figure 16 demonstrate the magnitude and phase of the 2D data containing random magnitudes. Figure 16b presents the surface plots for the magnitude and phase of a reconstructed image, based on Gaussian filtering and Fourier transform (Algorithm 2). The comparison of Figure 16a,b shows that the basis had little effect on the phase, while the magnitude changed from [0,0.03] in Figure 16a to [0,1] in Figure 16b, which demonstrates the better performance of the second algorithm over the other algorithm. Figure 17 shows the results obtained from the setup on Figure 5b. Both the proposed Algorithms 1 and 2 show almost similar results (rows 1 and 2), while they outperformed the Fuzzy c-mean algorithm (row 3). As is obvious from the Figure 17 (row 3a), Figure 17  
Figure 16: 3D demonstration of the phase and magnitude of the 2D data, (**a**) a reconstructed image based on a wavelet transform, and (**b**) a reconstructed image based on a Gaussian transform. Figure 17: The total process of target segmentation using (1) Fourier transform and Wavelet transform, followed by multi-thresholding and erosion, (2) Fourier transform and Gaussian, followed by multi-thresholding and erosion, (**a**) Fourier transforms, (**b**) inverted Fourier transforms (magnitude), (**c**) inverted Fourier transforms (phase), and (**d**) segmented results, and (3) a fuzzy c-mean algorithm with, (**a**) a threshold value of 0.206500, (**b**) a threshold value of 0.211538, and (**c**) a threshold value of 0.480769. (row 3b), and Figure 17 (row 3c), the outcome of FCM is dependent on the selection of the threshold value. The threshold value of the first figure is 0.206500, while the second and third figures have threshold values of 0.211538 and 0.480769, respectively. From all of the above results obtained through employing the algorithms on experimental setups in Figure 5a,b, it is concluded that the proposed algorithms were successfully adapted to determine the notch regions. However, the algorithms discriminated the boundaries of the notches, where Algorithm 3 (benchmark) was less successful (Figure 16, row 3a).