An automatic yearbook style photo generation method using color grading and guide image filtering based facial skin color correction

2015 ◽  
Author(s):  
Tatsuya Baba ◽  
Masahiro Okuda ◽  
Paul Perrotin ◽  
Tatesumi Yusuke ◽  
Keiichiro Shirai
Keyword(s):  
Skin Color ◽  
Image Filtering ◽  
Color Correction ◽  
Facial Skin ◽  
Color Grading

scholarly journals Guided Facial Skin Color Correction

Signals ◽  
2021 ◽  
Vol 2 (3) ◽  
pp. 540-558
Author(s):  
Keiichiro Shirai ◽  
Tatsuya Baba ◽  
Shunsuke Ono ◽  
Masahiro Okuda ◽  
Yusuke Tatesumi ◽  
...  
Keyword(s):  
Skin Color ◽  
Color Space ◽  
Image Filtering ◽  
Correction Method ◽  
Color Correction ◽  
Facial Skin ◽  
Image Correction ◽  
Color Distribution ◽  
The Face ◽  
Portrait Photographs

This paper proposes an automatic image correction method for portrait photographs, which promotes consistency of facial skin color by suppressing skin color changes due to background colors. In portrait photographs, skin color is often distorted due to the lighting environment (e.g., light reflected from a colored background wall and over-exposure by a camera strobe). This color distortion is emphasized when artificially synthesized with another background color, and the appearance becomes unnatural. In our framework, we, first, roughly extract the face region and rectify the skin color distribution in a color space. Then, we perform color and brightness correction around the face in the original image to achieve a proper color balance of the facial image, which is not affected by luminance and background colors. Our color correction process attains natural results by using a guide image, unlike conventional algorithms. In particular, our guided image filtering for the color correction does not require a perfectly-aligned guide image required in the original guide image filtering method proposed by He et al. Experimental results show that our method generates more natural results than conventional methods on not only headshot photographs but also natural scene photographs. We also show automatic yearbook style photo generation as another application.

Exploring the Facial Color Representative Regions Using the Humanae Images

2020 ◽  
Author(s):  
Yuchun Yan ◽  
Hayan Choi ◽  
Hyeon-Jeong Suk
Keyword(s):  
Image Analysis ◽  
Future Study ◽  
Skin Color ◽  
Color Difference ◽  
Facial Skin ◽  
Female Images ◽  
Gender And Race ◽  
Facial Landmarks

It is difficult to describe facial skin color through a solid color as it varies from region to region. In this article, the authors utilized image analysis to identify the facial color representative region. A total of 1052 female images from Humanae project were selected as a solid color was generated for each image as their representative skin colors by the photographer. Using the open CV-based libraries, such as EOS of Surrey Face Models and DeepFace, 3448 facial landmarks together with gender and race information were detected. For an illustrative and intuitive analysis, they then re-defined 27 visually important sub-regions to cluster the landmarks. The 27 sub-region colors for each image were finally derived and recorded in L ∗ , a ∗ , and b ∗ . By estimating the color difference among representative color and 27 sub-regions, we discovered that sub-regions of below lips (low Labial) and central cheeks (upper Buccal) were the most representative regions across four major ethnicity groups. In future study, the methodology is expected to be applied for more image sources.

Comparisons in perception of facial skin brightness, as influenced by differences in skin color: Asian observers

2021 ◽  
Author(s):  
Yuanyuan He ◽  
Taiga Mikami ◽  
Suguru Tanaka ◽  
Kumiko Kikuchi ◽  
Yoko Mizokami
Keyword(s):  
Skin Color ◽  
Facial Skin

Topographic-based facial skin color transfer

2004 ◽  
Author(s):  
Lijun Yin ◽  
Johnny Loi ◽  
Jingrong Jia ◽  
Joseph Morrissey
Keyword(s):  
Skin Color ◽  
Facial Skin ◽  
Color Transfer

scholarly journals Effects of Facial Threading on Female Skin Texture: A Prospective Trial with Physiological Parameters and Sense Assessment

2019 ◽  
Vol 2019 ◽  
pp. 1-8
Author(s):  
Li-Ying Lin ◽  
Shang-Chia Chiou ◽  
Shu-Hui Wang ◽  
Ching-Chi Chi
Keyword(s):  
Skin Color ◽  
Prospective Trial ◽  
Skin Condition ◽  
Facial Skin ◽  
Skin Texture ◽  
Skin Physiology ◽  
Hard Evidence ◽  
Mouth Corner ◽  
Vellus Hairs ◽  
To Receive

Background. Facial threading is a common tradition in Taiwan, Southeast Asia (called “Bande Abru”), Middle East (called “Khite”), and Egypt (called “Fatlah”). In addition to the ability to remove facial vellus hairs, facial threading can make the skin fairer and shinier. However, there has been a lack of hard evidence regarding the effects of facial threading on the skin. Objective. To examine the effects of facial threading on skin physiology as well as visual and touch senses by using scientific instruments. Methods. A total of 80 participants were allocated to receive facial threading, application of powder only, exfoliation, and shaving. Prior to and following the assigned treatment, a noninvasive skin condition detection device was used to measure skin coarseness, hydration, melanin, and erythema index. Sense assessment and image analysis were also performed. Results. This study showed that facial threading was found to improve the facial skin roughness indices with significant decreases by 30.4%, 35.9%, and 16.7%, respectively, for the participants’ forehead, cheek, and mouth corner skin. No significant adverse changes in moisture levels and skin pigment indices were detected. In addition, there was improvement in subjects’ touch sense of their skin and feelings about skin color. Conclusions. Traditional facial threading can remove facial vellus hairs and lower skin roughness levels, thereby improving the skin texture. However, pricking sensation appeared during the facial threading process, which might cause concerns about irritation.

scholarly journals The efficacy of skin care products containing glutathione in delivering skin lightening in Indonesian women

2019 ◽  
Author(s):  
Kristiana Etnawati ◽  
Dwi Retno Adiwinarni ◽  
Devi Artami Susetiati ◽  
Yusuke Sauchi ◽  
Hitomi Ito
Keyword(s):  
Skin Color ◽  
Skin Care ◽  
Efficacy And Safety ◽  
Facial Skin ◽  
Cosmetic Products ◽  
Double Blind ◽  
Tingling Sensation ◽  
Asian Market ◽  
Skin Care Products ◽  
Skin Lightening

Glutathione is a potent antioxidant, which is widely used in skin care products for skin lightening especially in the Asian market. Presently, there was only one study of topical 2% oxidized glutathione (GSSG) in Philipino women, further study is needed to evaluate the efficacy and safety of cosmetic products containing glutathione. A double blind randomized clinical trial study was conducted in Yogyakarta, Indonesia, in 74 healthy Indonesian women, with average age 33.3 ± 5.9 years when subjects participated in the study. Each subject received supervised applications of Facial Wash twice a day, Day Cream with sunscreen and Night Cream. The subjects were divided into 3 groups based on the active ingredients of the tested products, which included glutathione reduced (GSH) 0.1%, GSH 0.5%, and without GSH. The effects of the tested products in lightening skin color and pigmentation were measured colorimetry with Chromameter Minolta for L*. Compared to a baseline, there were significant increases of L* (lightness) or ΔL* detected as early as week 2 in which group of GSH 0.1% were significantly higher compared to group of GSH 0.5% and group without GSH. Hyperpigmented lesions also improved, where GSH 0.5% group showed its superiority compared to others groups in week 8. The undesired effect were few minutes mild tingling sensation after night cream, and worsening of acne in all tested products. Conclusion skin care products containing GSH 0.1% and 0.5% were effective in facial skin lightening.

Image analysis of skin color heterogeneity focusing on skin chromophores and the age-related changes in facial skin

2014 ◽  
Vol 21 (2) ◽  
pp. 175-183 ◽  
Author(s):  
Kumiko Kikuchi ◽  
Yuji Masuda ◽  
Toyonobu Yamashita ◽  
Eriko Kawai ◽  
Tetsuji Hirao
Keyword(s):  
Image Analysis ◽  
Skin Color ◽  
Facial Skin ◽  
Age Related ◽  
Age Related Changes
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