# Guided Facial Skin Color Correction
## 1 Introduction  
Portrait photographs sometimes get undesirable color due to a background color reflection. In particular, changes in skin color sometimes give a bad impression, so that professional cameramen arrange lighting conditions to make the skin color and brightness uniform for each photograph. Meanwhile, for an amateur, more effort is required to achieve the same quality. Therefore, there is a need for a simple and automatic method not requiring any special technique to unify the color and brightness between multiple images. The undesirable color on portrait photographs is caused by the following:  
* Each camera has its own camera response sensitivity, producing a different distribution of skin color in a color space.
* Background color is usually reflected to faces causing distorted colors.  
* When each subject wears different colored clothes, color correction for the whole image region distorts the skin color, while skin color correction discolors the clothes.  
To address the problems, we need a color correction scheme that affects only the face region.  
In this paper, we attempt to correct an image with various color and brightness conditions with a guide image. Our method has various applications, e.g., the creation of a photo name list such as a yearbook without much effort or cost. If ones try to gather photographs taken with different cameras in different lighting conditions, correcting the images becomes a very difficult task even using off-the-shelf image processing software. In the situation considered, we need to unify several attributes of all images: the size of cropped facial image, facial skin color, brightness, and background color. Automatic correction of the attributes requires  
1. Face detection and Facial skin color extraction;
2. Facial skin color correction.  
A simple combination of these techniques gives boundary artifacts between the corrected region and the uncorrected region because the color correction only corrects the extracted region. This is described in Section 2.  
In addition to the algorithm described in this paper, we propose a hybrid _guided image filtering_ (GIF) method (the red box in Figure 1), which performs color transfer on the local face region while keeping colors in other regions, making GIF suitable for the correction of facial skin color and brightness. Because region extraction and color transfer are individual procedures, color transfer on part of an image generates a color gap between the original color part and the color transformed part. The hybrid GIF transforms a part of the image as an object based color transfer. In contrast to the fact that the original GIF [1] needs a perfectly-aligned guide image, our GIF only needs roughly aligned pixels. As for non-aligned regions, the filtering is achieved by aligned region propagation such as colorization [2] and matting [3]. Our method carries out nonlinear correction only on the face region and achieves better results than conventional methods. A preliminary version of this study without several improvements or new applications appeared in conference proceedings [4].  
The rest of this paper is organized as follows: Section 2 introduces related work on color correction and facial image correction. Section 3 describes the proposed guide facial skin color correction method. The proposed algorithm is evaluated in experiments by comparison with various conventional methods in Section 4. Finally, this paper is concluded in Section 5.