# An Image Edge Detection Algorithm Based on an Artificial Plant Community
## 5 Experimental Analysis
### Analysis and Discussion
Furthermore, the quantitative comparison results of the different detection models on the Pascal VOC dataset and Stanford background dataset are shown in Tables 4 and 5, respectively. There are six quantitative indexes, namely the average accuracy (_ACC_ in Equation (11)), entropy (_ENT_ in Equation (12)), standard deviation (_STD_ in Equation (13)), peak signal-to-noise ratio (_PSNR_ in Equation (14)), distortion (_DST_ in Equation (15)), and average solving time (ms). In terms of the average performance, the proposed APC and CNN [14; 15; 16; 17; 34; 35; 36; 37] can achieve the highest accuracy levels, but the proposed APC needs less time than the latter. In terms of the average detection time, the proposed APC and SA [26] can achieve the fastest detection rates, but the proposed APC has an advantage in terms of its average accuracy. The performance test results using the Pascal VOC dataset are worse than those using the Stanford background dataset, due to the increased complexity of the problems to be solved. In both test datasets, the heuristic algorithms, including the proposed APC, \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{3}{*}{\begin{tabular}{c} **Detection** \\ **Models** \\ \end{tabular} } & \multirow{3}{*}{\begin{tabular}{c} **Average** \\ **Accuracy** \\ **(_ACC_)** \\ \end{tabular} } & \multirow{3}{*}{\begin{tabular}{c} **Entropy** \\ **(_ENT_)** \\ \end{tabular} } & \multicolumn{3}{c}{**Standard**} & \multicolumn{1}{c}{**Signal-to-**} & \multirow{3}{*}{\
\begin{tabular}{c} **Distortion** \\ **Noise** \\ **(_STD_)** \\ \end{tabular} } & \multirow{3}{*}{
\begin{tabular}{c} **Average** \\ **Solving** \\ **Time (ms)** \\ \end{tabular} } \\  & & & & & & \\ \hline APC & 0.902 & 0.384 & 61.72 & 18.48 & 14.65 & 813 \\ ABC [5; 41] & 0.791 & 0.286 & 62.03 & 18.62 & 15.27 & 858 \\ FCM & & & & & & \\
[9; 14; 31; 32] & 0.825 & 0.322 & 83.35 & 14.77 & 14.53 & 739 \\ CNN & & & & & & \\
[14; 15; 16; 17; 34; 35; 36; 37] & 0.914 & 0.391 & 58.67 & 19.36 & 13.73 & 3022 \\ PSO & & & & & & \\
[18; 40] & 0.859 & 0.325 & 80.91 & 12.59 & 15.18 & 806 \\ ACO & & & & & & \\
[19; 21] & 0.846 & 0.318 & 70.54 & 13.61 & 15.09 & 1496 \\ GA [22; 42] & 0.873 & 0.323 & 82.49 & 12.42 & 15.21 & 847 \\ AFSA [23] & 0.790 & 0.307 & 69.26 & 13.34 & 14.84 & 1305 \\ SA [26] & 0.787 & 0.299 & 71.60 & 12.78 & 15.12 & 714 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Comparison of results of different models on the Pascal VOC dataset. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{3}{*}{\begin{tabular}{c} **Detection** \\ **Models** \\ \end{tabular} } & \multirow{3}{*}{\begin{tabular}{c} **Average** \\ **Accuracy** \\ **(_ACC_)** \\ \end{tabular} } & \multirow{3}{*}{\begin{tabular}{c} **Entropy** \\ **(_ENT_)** \\ \end{tabular} } & \multicolumn{3}{c}{**Standard**} & \multicolumn{1}{c}{**Scalar-to-**} & \multirow{3}{*}{\
\begin{tabular}{c} **Distortion** \\ **Noise** \\ **Ratio** \\ **(_PSNR_)** \\ \end{tabular} } & \multirow{3}{*}{
\begin{tabular}{c} **Average** \\ **Solving** \\ **Time (ms)** \\ \end{tabular} } \\ \hline APC & 0.913 & 0.457 & 55.31 & 19.42 & 14.53 & 649 \\ ABC [5; 41] & 0.822 & 0.305 & 57.54 & 18.49 & 15.16 & 724 \\ FCM & & & & & & \\
[9; 14; 31; 32] & 0.817 & 0.381 & 61.29 & 15.38 & 14.25 & 692 \\ CNN & & & & & & \\
[14; 15; 16; 17; 34; 35; 36; 37] & 0.926 & 0.502 & 56.48 & 20.23 & 14.51 & 2107 \\ PSO & & & & & & \\
[18; 40] & 0.864 & 0.413 & 74.60 & 12.81 & 14.97 & 706 \\ ACO & & & & & & \\
[19; 21] & 0.857 & 0.398 & 63.07 & 14.84 & 13.82 & 1138 \\ GA [22; 42] & 0.889 & 0.409 & 73.16 & 12.90 & 14.68 & 785 \\ AFSA [23] & 0.828 & 0.326 & 59.53 & 13.76 & 14.64 & 1140 \\ SA [26] & 0.811 & 0.320 & 65.72 & 13.05 & 14.79 & 653 \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Comparison of results of different models on Stanford background dataset. ABC [541], FCM [9; 14; 31; 32], PSO [18; 40], ACO [19; 21], GA [22; 42], AFSA [23] and SA [26], have more advantages than the CNN [14; 15; 16; 17; 34; 35; 36; 37], as they have shorter solving times.