# A Semantic Segmentation Algorithm Using FCN with Combination of BSLIC
## 4 Experimental Results
### Quantitative Comparison  
In practical engineering, pixel accuracy (PA), intersection over union (IoU), and mean intersection over union (mIoU) are used to evaluate the performance of the semantic segmentation technique. PA is used to measure the accuracy of object contour segmentation. IoU is used to measure the accuracy of an object detector on a particular dataset. mIoU is the average of IoU and is defined to reflect the overall enhancement of semantic segmentation accuracy. The formulas to calculate metrics can be found in [31] and is used in this paper. It is assumed that the total of classes is \((k+1)\) and \(p_{ij}\) is the amount of pixels of class \(i\) inferred to class \(j\). \(p_{ii}\) represents the number of true positives, while \(p_{ij}\) and \(p_{ji}\) are usually interpreted as false positives and false negatives, respectively. * _Pixel Accuracy (PA):_ It computes a ratio between the amount of properly classified pixels and the total number of them. The formula can be expressed as: \[PA=\frac{\sum_{i=0}^{k}p_{ii}}{\sum_{i=0}^{k}\sum_{j=0}^{k}p_{ij}},\] (3)
* _Intersection Over Union (IoU):_ The IoU is used to measure whether the target in the image is detected. The formula can be expressed as: \[IoU=\frac{p_{ii}}{\sum_{j=0}^{k}p_{ij}+\sum_{j=0}^{k}p_{ji}-p_{ii}},\] (4) \begin{table}
\begin{tabular}{c c} \hline
**Method** & **Average Time (ms/image)** \\ \hline FCN-32s & 293.050 \\ FCN-16s & 297.358 \\ FCN-8s & 302.796 \\ Ours & 310.218 \\ \hline \end{tabular}
\end{table} 
Table 1: Time-consuming of four methods. Figure 8: Combination FCN and BSLIC to acquire more details of a target. (**a**) The original test images; (**b**) The BSLIC superpixel segmentation results; (**c**) The FCN-88 semantic segmentation results; (**d**) The results of the improved model proposed in this paper; and, (**e**) The ground truth. * _Mean Intersection Over Union (mIoU):_ This is the standard metric for segmentation purposes. It computes a ratio between the ground truth and our predicted segmentation. mIoU is computed by averaging IoU. \[mIoU=\frac{1}{k+1}\times\sum{{}_{k}IoU_{k}},\] (5)  
Based on the previous test dataset from PASCAL VOC 2012, PA, IoU, and mIoU are calculated by (3)-(5), respectively. Table 2 gives the IoU scores between SegNet [32], UNIST_GDN_FCN [33], and our proposed method. Table 3 gives the IoU scores of FCN-32s, FCN-16s, FCN-8s, and our method. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Category** & **SegNet** & **UNIST\_GDN\_FCN** & **Ours** \\ \hline
0 & 90.3 * & 89.8 & 89.7 \\
1 & 73.6 * & 74.5 & 74.7 * \\
2 & 37.6 * & 31.9 & 36.9 \\
3 & 62.0 & 66.7 & 77.4 * \\
4 & 46.8 & 49.7 & 52.4 * \\
5 & 58.6 & 60.5 & 67.7 * \\
6 & 79.1 * & 76.9 & 75.5 \\
7 & 70.1 & 75.9 * & 71.5 \\
8 & 65.4 & 76.0 & 76.5 * \\
9 & 23.6 & 22.9 & 24.1 * \\
10 & 60.4 & 57.6 & 71.0 * \\
11 & 45.6 & 54.5 * & 44.6 \\
12 & 61.8 & 73.0 * & 69.3 \\
13 & 63.5 * & 59.4 & 61.8 \\
14 & 75.3 & 75.0 & 76.0 * \\
15 & 74.9 & 73.7 & 75.8 * \\
16 & 42.6 & 51.0 * & 44.1 \\
17 & 63.7 & 67.5 & 68.5 * \\
18 & 42.5 & 43.3 * & 33.9 \\
19 & 67.8 & 70.0 & 75.4 * \\
20 & 52.7 & 56.4 * & 52.6 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: The Intersection Over Union (IoU) scores of three methods. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Category** & **FCN-32s** & **FCN-16s** & **FCN-8s** & **Ours** \\ \hline
0 & 88.611 & 89.704 & 89.961 * & 89.721 \\
1 & 66.803 & 74.143 & 74.346 & 74.676 * \\
2 & 30.772 & 35.861 & 36.759 & 36.899 * \\
3 & 72.928 & 77.133 & 77.016 & 77.426 * \\
4 & 50.6  
It can be shown in both Tables 2 and 3 that our method has an advantage in most of the classification indicators. Because Table 3 is consistent with the results obtained in Table 2, so only the Table 3 is used to analyze the performance of the proposed method, as follows:  
The comparison of IoU between our proposed algorithm and the FCN model are shown in Figure 9. The abscissa value may range from 0-20, representing the different categories in PASCAL VOC 2012.