###### Abstract
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**No.** & \begin{tabular}{c} **Type of Defects** \\ **Detected** \\ \end{tabular} & **Type of Used Feature** & \
\begin{tabular}{c} **Background** \\ **Texture of CTs** \\ \end{tabular} &
\begin{tabular}{c} **Defects** \\ **Discrimination** \\ \end{tabular} & **Evaluation Metrics** \\ \hline
[1] &
\begin{tabular}{c} Corner or edge, glaze, \\ pin-hole, cracks \\ \end{tabular} & GLCM & Simple textures & Without & Accuracy: 83\% \\
[4] & \
\begin{tabular}{c} Cracks \\ \end{tabular} &
\begin{tabular}{c} Morphological \\ transformation \\ \end{tabular} & Without & Without & Not indicated \\
[5] &
\begin{tabular}{c} Cracks, pit and \\ damage defects \\ \end{tabular} & Gabor energy spectra & Without & Without & Not indicated \\
[6] &
\begin{tabular}{c} Invariant rotation \\ \end{tabular} & Without & Without & Accuracy: 93.4\% \\
[7] & \begin{tabular}{c} Cracks, holes and \\ spots, breakage, \\ melt \\ cracks \\ \end{tabular} & \
\begin{tabular}{c} GLCM, HOG, DWT, \\ SFTA \\ \end{tabular} & Without and & Without &
\begin{tabular}{c} Accuracy: 99.01\%, \\ 93.2\% \\ \end{tabular} \\
[8] & \begin{tabular}{c} Spots, breakage, \\ melt \\ \end{tabular} & \begin{tabular}{c} Color spatial \\ distribution variance \\ \end{tabular} & \begin{tabular}{c} One texture; two \\ textures, \\ three textures \\ \end{tabular} & \
\begin{tabular}{c} Color spot area \\ weight features \\ added as a \\ discriminator \\ \end{tabular} &
\begin{tabular}{c} Accuracy: 98.4\%, \\ 96.2\% and 91.21\% \\ respectively \\ \end{tabular} \\
[9] & \begin{tabular}{c} Cracks and spots \\ \end{tabular} & Fourier transform & \
\begin{tabular}{c} Black Random \\ Stripes, brown \\ light stripes \\ without \\ \end{tabular} & Without &
\begin{tabular}{c} F1-score: 92.36\% and \\ 88.66\% \\ \end{tabular} \\
[10] & \begin{tabular}{c} Cracks \\ \end{tabular} & \begin{tabular}{c} LBP \\ Morphology and \\ wavelet transform \\ \end{tabular} & \begin{tabular}{c} without \\ Without \\ \end{tabular} & \
\begin{tabular}{c} Without \\ \end{tabular} &
\begin{tabular}{c} Accuracy: 87.5\% \\ \end{tabular} \\
[11] & \begin{tabular}{c} Cracks and spots \\ \end{tabular} & \begin{tabular}{c} SIFT and color \\ moments \\ \end{tabular} & \
\begin{tabular}{c} Gray and colored \\ textures \\ \end{tabular} & Without &
\begin{tabular}{c} Highest accuracy: \\ 92.6\% \\ \end{tabular} \\
[13] &
\begin{tabular}{c} Pits, notches, cracks, \\ grinding \\ \end{tabular} & U-Net model & Without & Without & Accuracy: 94\% \\
[14] & \
\begin{tabular}{c} Cracks, dirt \\ \end{tabular} & Deep neural network & Complex textures & With a comparator &
\begin{tabular}{c} The average false \\ detection rate: 5.8\% \\ \end{tabular} \\
[15] &
\begin{tabular}{c} Cracks, holes \\ auto-encoding \\ network \\ \end{tabular} & Simple textures & Without & F1-score: 94.8\% and 87.6\% \\
[16] & \
\begin{tabular}{c} Cracks \\ \end{tabular} & U-Net & Simple textures & Without &
\begin{tabular}{c} Precision: 99.9\%; \\ Recall: 78.7\% \\ \end{tabular} \\
[17] & \
\begin{tabular}{c} Cracks \\ \end{tabular} &
\begin{tabular}{c} YOLOv3-tiny \\ \end{tabular} & Simple textures & Without & Accuracy: 89.9\% \\ \hline \hline \end{tabular}
\end{table} 
Table 1: A summary of previous researchers’ work. implement their respective functions separately. Experience with the proposed methodology is described in Section 3. The results and analysis from the experiment are revealed in Section 4. A conclusion is presented in Section 5.