# An Efficient Multiscale Scheme Using Local Zernike Moments for Face Recognition
## 4 Experimental Results
### Experiments on SCface  
SCface [56] is a dataset that has been created in accordance with real-world conditions [56]. Images in this dataset were recorded in uncontrolled indoor environments using seven surveillance cameras with different qualities and resolutions. Two of these cameras recorded in infrared spectrum (IR). While the images were being recorded, the cameras were placed at a higher position than the heads of the people (at a height of 2.25 m) and images were taken at three different distances: 4.2 m, 2.6 m, and 1 m. There are a total of 4160 images taken from 130 different people in the dataset. Within SCface, there are two different identification protocols, DayTime and NightTime. In the DayTime protocol, a gallery set consisting of mugshot images of 130 different people is used, and there are a total of 15 probe sets created from images taken at 3 different distances using 5 different cameras (cam1-5). In the NightTime, both the gallery images used in the DayTime protocol and a gallery set consisting of 130 mugshot images recorded in infrared spectrum can be used as a gallery set. In this protocol, there are a total of six probe sets which are created with the IR images taken at three different distances using two different IR cameras. Grgic et al. [56] recommend that external images should be used as a training set, so that the results obtained in these protocols are more consistent. Therefore, the Fa set of FERET was used to learn the PCA matrices in the experiments performed in this study. According to the standard protocol of SCface, the identification performance was given as Rank 1 recognition rate, as it was in FERET. Sample images of SCface are presented in Figure 10. There are too many images with low resolution in this dataset. For this reason, the feature vectors, which were constructed using the images in five different scales in the previous sections, were constructed here in only three different scales. Face images were resized to three different sizes as follows: \(126\times 126,94\times 94\), and \(70\times 70\). For the \(126\times 126\) image, the eye coordinates were set to \((50,66)\) and \((75,66)\). When facial images are used in larger sizes, identification performance is adversely affected because low-resolution images reduce between-class differences. Figure 10: Images from SCface. (**a**) In visible and (**b**) in infra-red spectrum. In the first column, mugshot gallery images are given. In second, third, and fourth columns, the images recorded at distance 1, 2, and 3 are given, respectively. Table 3 shows the results obtained for the DayTime protocol with the best known results in the literature. While these results were calculated, the moment degrees in the first and second LZM transformations were set to four, and the filter size was seven in both transformations. According to the results given in Table 3, it can be seen that the proposed method achieved the highest result in average success. The results obtained were approximately 6% higher than the best known result (Local Patterns of Gradients (LPOG) [46]). In [46], the DayTime gallery set was used as the training set while the LPOG results given here were calculated. When they used Fa set as the training set, the average success achieved with LPOG was 50.8%. Since only Fa was used as the training set in this study, the improvement achieved was actually more than 10%. In the SCface Daytime protocol, there are a total of 15 probe sets. These consist of images taken at three different distances by using five different cameras. Taking the results obtained into account, it can be seen that the results obtained for distance 2 (2.6 m) were better than distances 1 (4.2 m) and 3 (1 m). Although distance 3 is closer than 2, the main reason why the results for distance 3 were not better is the angular difference caused by the camera being above the head alignment. Comparing MS-LZM with other methods, it can be seen that the results obtained for distances 1 and 2 were better.