Evolution of Human Skin Color and Vitamin D

Vitamin D ◽  
2018 ◽  
pp. 29-44 ◽  
Author(s):  
Nina G. Jablonski
Keyword(s):  
Vitamin D ◽  
Human Skin ◽  
Skin Color

scholarly journals PKT: fast color-based spatial model for human skin detection

2021 ◽  
Author(s):  
Grace L. Samson ◽  
Joan Lu
Keyword(s):  
Spatial Structure ◽  
Human Skin ◽  
Skin Color ◽  
Skin Detection ◽  
Quad Tree ◽  
Learning Tasks ◽  
Color Detection ◽  
Speed Up ◽  
Image Pixels ◽  
Speed Accuracy

AbstractWe present a new detection method for color-based object detection, which can improve the performance of learning procedures in terms of speed, accuracy, and efficiency, using spatial inference, and algorithm. We applied the model to human skin detection from an image; however, the method can also work for other machine learning tasks involving image pixels. We propose (1) an improved RGB/HSL human skin color threshold to tackle darker human skin color detection problem. (2), we also present a new rule-based fast algorithm (packed k-dimensional tree --- PKT) that depends on an improved spatial structure for human skin/face detection from colored 2D images. We also implemented a novel packed quad-tree (PQT) to speed up the quad-tree performance in terms of indexing. We compared the proposed system to traditional pixel-by-pixel (PBP)/pixel-wise (PW) operation, and quadtree based procedures. The results show that our proposed spatial structure performs better (with a very low false hit rate, very high precision, and accuracy rate) than most state-of-the-art models.

Face Image Segmentation Using Color Information and Saliency Map

2011 ◽  
Vol 55-57 ◽  
pp. 77-81
Author(s):  
Hui Ming Huang ◽  
He Sheng Liu ◽  
Guo Ping Liu
Keyword(s):  
Image Segmentation ◽  
Human Skin ◽  
Skin Color ◽  
Saliency Map ◽  
Face Image ◽  
Color Information ◽  
Attention Model ◽  
Face Area ◽  
Face Region ◽  
The Face

In this paper, we proposed an efficient method to address the problem of color face image segmentation that is based on color information and saliency map. This method consists of three stages. At first, skin colored regions is detected using a Bayesian model of the human skin color. Then, we get a chroma chart that shows likelihoods of skin colors. This chroma chart is further segmented into skin region that satisfy the homogeneity property of the human skin. The third stage, visual attention model are employed to localize the face region according to the saliency map while the bottom-up approach utilizes both the intensity and color features maps from the test image. Experimental evaluation on test shows that the proposed method is capable of segmenting the face area quite effectively，at the same time, our methods shows good performance for subjects in both simple and complex backgrounds, as well as varying illumination conditions and skin color variances.

Human Skin Detection in Color Images Using Deep Learning

2015 ◽  
Vol 5 (2) ◽  
pp. 1-13 ◽  
Author(s):  
Mohammadreza Hajiarbabi ◽  
Arvin Agah
Keyword(s):  
Neural Networks ◽  
Deep Learning ◽  
Human Skin ◽  
Skin Color ◽  
Color Image ◽  
Gaussian Model ◽  
Color Images ◽  
Skin Detection ◽  
Learning Methods ◽  
Rule Based

Human skin detection is an important and challenging problem in computer vision. Skin detection can be used as the first phase in face detection when using color images. The differences in illumination and ranges of skin colors have made skin detection a challenging task. Gaussian model, rule based methods, and artificial neural networks are methods that have been used for human skin color detection. Deep learning methods are new techniques in learning that have shown improved classification power compared to neural networks. In this paper the authors use deep learning methods in order to enhance the capabilities of skin detection algorithms. Several experiments have been performed using auto encoders and different color spaces. The proposed technique is evaluated compare with other available methods in this domain using two color image databases. The results show that skin detection utilizing deep learning has better results compared to other methods such as rule-based, Gaussian model and feed forward neural network.

scholarly journals Cross-sectional study reveals a high prevalence of vitamin D deficiency among healthy school children in central Kerala, India

2019 ◽  
Vol 6 (2) ◽  
pp. 867
Author(s):  
Ayyappan Anitha ◽  
Suresh A. Poovathinal ◽  
Vijitha Viswambharan ◽  
Ismail Thanseem ◽  
Mahesh M. Vasu ◽  
...  
Keyword(s):  
Vitamin D ◽  
School Children ◽  
Skin Color ◽  
Economic Status ◽  
Cross Sectional Study ◽  
Vitamin D Status ◽  
Sectional Study ◽  
Cross Sectional ◽  
Vitamin D Levels ◽  
High Prevalence

Background: Authors examined serum vitamin D status among the healthy school children belonging to the south Indian state of Kerala.Methods: A cross-sectional study, participants were recruited through medical camps organized in Thrissur and Palakkad districts of central Kerala during the months of March and April 2017. A 174 healthy school children (98 males and 76 females) aged 5-13 years were recruited for the study. The children were found to be healthy on the basis of physical examination by a Paediatrician. None of the children had any symptoms of skeletal deformities. All the children were drug-naive. Data on height, weight, skin color, food habits, physical activities and socio-economic status were recorded. A 2ml of peripheral blood samples were collected from the participants. Total vitamin D in the serum was estimated by chemiluminescence immunoassay (CLIA).Results: VDD was observed in 60.92% and insufficiency in 30.46% of the participants. Only 8.62% of the participants had normal vitamin D levels. The mean vitamin D level was 19.93 ng/ml. Males had significantly higher vitamin D levels compared to females. Factors such as age, height, weight, diet, skin color and socio-economic status did not influence vitamin D levels.Conclusions: This is the first study of vitamin D status among the school-age children of Kerala. This paper adds further evidence to the reports indicating high prevalence of subclinical VDD among children across India and calls for action.

scholarly journals Differences in RAAS/vitamin D linked to genetics and socioeconomic factors could explain the higher mortality rate in African Americans with COVID-19

2020 ◽  
Vol 14 ◽  
pp. 175394472097771
Author(s):  
Virna Margarita Martín Giménez ◽  
León Ferder ◽  
Felipe Inserra ◽  
Joxel García ◽  
Walter Manucha
Keyword(s):  
Vitamin D ◽  
Skin Color ◽  
Black People ◽  
Ethnic Disparities ◽  
Black Population ◽  
The United States ◽  
Ethnic Origin ◽  
Plasma Vitamin ◽  
Susceptibility To Infection ◽  
Vitamin D Levels

COVID-19 is said to be a pandemic that does not distinguish between skin color or ethnic origin. However, data in many parts of the world, especially in the United States, begin to show that there is a sector of society suffering a more significant impact from this pandemic. The Black population is more vulnerable than the White population to infection and death by COVID-19, with hypertension and diabetes mellitus as probable predisposing factors. Over time, multiple disparities have been observed between the health of Black and White populations, associated mainly with socioeconomic inequalities. However, some mechanisms and pathophysiological susceptibilities begin to be elucidated that are related directly to the higher prevalence of multiple diseases in the Black population, including infection and death by COVID-19. Plasma vitamin D levels and evolutionary adaptations of the renin-angiotensin-aldosterone system (RAAS) in Black people differ considerably from those of other races. The role of these factors in the development and progression of hypertension and multiple lung diseases, among them SARS-CoV-2 infection, is well established. In this sense, the present review attempts to elucidate the link between vitamin D and RAAS ethnic disparities and susceptibility to infection and death by COVID-19 in Black people, and suggests possible mechanisms for this susceptibility.

scholarly journals High Prevalence of Hypovitaminosis D in Institutionalized Elderly Individuals is Associated with Summer in a Region with High Ultraviolet Radiation Levels

Nutrients ◽  
2019 ◽  
Vol 11 (7) ◽  
pp. 1516
Author(s):  
Sara Estéfani S. Sousa ◽  
Márcia Cristina Sales ◽  
José Rodolfo T. Araújo ◽  
Karine C.M. Sena-Evangelista ◽  
Kenio C. Lima ◽  
...  
Keyword(s):  
Vitamin D ◽  
Dietary Intake ◽  
Skin Color ◽  
Hypovitaminosis D ◽  
Vitamin D Supplementation ◽  
Vitamin D Status ◽  
Institutionalized Elderly ◽  
Elderly Individuals ◽  
Independent Variables ◽  
High Prevalence

Vitamin D may play a significant role in regulating the rate of aging. The objective of the study was to assess vitamin D status and its associated factors in institutionalized elderly individuals. A total of 153 elderly individuals living in Nursing Homes (NH) were recruited into the study. Serum 25-hydroxyvitamin D [25(OH)D] concentration was used as the biomarker of vitamin D status, and it was considered as the dependent variable in the model. The independent variables were the type of NH, age-adjusted time of institutionalization, age, sex, skin color, body mass index, waist and calf circumference, physical activity practice, mobility, dietary intake of vitamin D and calcium, vitamin D supplementation, use of antiepileptics, and season of the year. Serum 25(OH)D concentrations less than or equal to 29 ng/mL were classified as insufficient vitamin D status. The prevalences of inadequate dietary intake of vitamin D and calcium were 95.4% and 79.7%, respectively. The prevalence of hypovitaminosis D was 71.2%, and the mean serum concentration of 25(OH)D was 23.9 ng/mL (95% confidence interval [CI]: 22.8–26.1). Serum 25(OH)D concentration was associated with the season of summer (p = 0.046). There were no associations with other independent variables (all p > 0.05). The present results showed that a high prevalence of hypovitaminosis D was significantly associated with summer in institutionalized elderly individuals.

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