## 2 Materials and Methods
### Face Datasets  
We employed several face datasets for this research:  
* The Database of Faces (AT&T) [40] The Database of Faces (AT&T Laboratories, Cambridge), formerly known as The ORL Database of Faces, consists of 400 face images from 40 people. The images are in grayscale, with each image having 92 \(\times\) 112 pixels. The database has variations in lighting conditions and facial expressions, with some variations in glasses and no glasses. Several people were photographed at different times. The background of each image is dark, and the image was taken from the front with an upright position. Figure 1a displays examples of images from this database.
* The BeautyREC Dataset (BeautyREC) [41] The BeautyREC Dataset (BeautyREC) is a face makeup transfer dataset containing 3000 color images from various people. It is worth noting that this dataset is imbalanced. The size of each image is 512 \(\times\) 512 pixels, then resized to 100 \(\times\) 100 pixels and the color changed into grayscale images. The makeup transferring method is detailed in [41]. The makeup transfer dataset encompasses various makeup styles, face poses, and races. Figure 1b shows an example of images from this dataset.
* The Extended Yale B Face dataset (EYB) [42; 43] The Extended Yale B (EYB) Face dataset has 2414 frontal face images with variations in pose and lighting conditions. All 2414 images are from a total of 38 people. In this research, we employed only 58 images from each person due to the extremely dark images. Each image has a size of 168 \(\times\) 192 pixels in grayscale. Figure 1c displays an example of images from this dataset.
* The Extended Yale B Face dataset with dark images (EYB-Dark) [42; 43] To challenge the method against dark images, we separated four images from each person in the EYB Face dataset and created a subset of EYB-Dark. The four images were taken randomly, but they needed to strictly abide by this rule: one under a slight illumination variation and three dark images. The total of this sub-dataset is 38 people \(\times\) 4 images = 152 images. The size of each image is the same as the EYB Face dataset, and they are all in grayscale. Figure 1d shows an example of images from this dataset.
* The FEI Face Database (FEI) [44] The FEI Face Database contains 2800 images from 200 people; each person has 14 images. Each image is a color image captured in an upright frontal position with a 180-degree rotation of the profile on a uniform white background. The scale may differ by approximately 10%; each image was originally 640 \(\times\) 480 pixels. This database is a collection of face images from students and employees, aged 19 to 40, from the Artificial Intelligence Laboratory of FEI in Sao Bernardo do Campo, Sao Paulo, Brazil. All people have distinct appearances, hairstyles, and jewelry. The ratio between men and women is approximately the same. In this research, we resized the images into 320 \(\times\) 240 pixels and changed the color into grayscale images. Figure 1e shows the example of images from FEI.
* The FEI Face Database (FEI) Subset Frontal and Expression (FEI-FE) [44] The FEI Face Database has a subset that contains only two images per person and 400 images in total, consisting of one frontal face image with a neutral (non-smiling) expression and one frontal face image with a smiling expression. In this research, we resized the images into 180 \(\times\) 130 pixels and changed the color into grayscale images. Figure 1f shows the example of images from FEI-FE.