Skin color measurements: comparison between three instruments: the Chromameter® , the DermaSpectrometer® and the Mexameter®

2000 ◽  
Vol 6 (4) ◽  
pp. 230-238 ◽  
Author(s):  
P. Clarys ◽  
K. Alewaeters ◽  
R. Lambrecht ◽  
A. O. Barel
Keyword(s):  
Skin Color ◽  
Color Measurements

scholarly journals A comparison of animal color measurements using a commercially available digital color sensor and photograph analysis

2020 ◽  
Vol 66 (6) ◽  
pp. 601-606 ◽  
Author(s):  
Alex D Potash ◽  
Daniel U Greene ◽  
Gabrielle A Foursa ◽  
Verity L Mathis ◽  
L Mike Conner ◽  
...  
Keyword(s):  
Skin Color ◽  
New Technology ◽  
Human Vision ◽  
Light Spectrum ◽  
Small Aperture ◽  
Animal Coloration ◽  
Color Sensor ◽  
Color Measurements ◽  
Measuring Tool ◽  
Reliable Methods

Abstract An animal’s pelage, feather, or skin color can serve a variety of functions, so it is important to have multiple standardized methods for measuring color. One of the most common and reliable methods for measuring animal coloration is the use of standardized digital photographs of animals. New technology in the form of a commercially available handheld digital color sensor could provide an alternative to photography-based animal color measurements. To determine whether a digital color sensor could be used to measure animal coloration, we tested the ability of a digital color sensor to measure coloration of mammalian, avian, and lepidopteran museums specimens. We compared results from the sensor to measurements taken using traditional photography methods. Our study yielded significant differences between photography-based and digital color sensor measurements of brightness (light to dark) and colors along the green to red spectrum. There was no difference between photographs and the digital color sensor measurements for colors along the blue to yellow spectrum. The average difference in recorded color (ΔE) by the 2 methods was above the threshold at which humans can perceive a difference. There were significant correlations between the sensor and photographs for all measurements indicating that the sensor is an effective animal coloration measuring tool. However, the sensor’s small aperture and narrow light spectrum range designed for human-vision limit its value for ecological research. We discuss the conditions in which a digital color sensor can be an effective tool for measuring animal coloration in both laboratory settings and in the field.

Skin color measurements before and after two weeks of sun exposure

2022 ◽  
Vol 192 ◽  
pp. 107976
Author(s):  
Li Jiang ◽  
Han Wang ◽  
Cheng Gao ◽  
Xiaohui Zhang ◽  
Kaida Xiao ◽  
...  
Keyword(s):  
Skin Color ◽  
Sun Exposure ◽  
Color Measurements ◽  
Before And After

Quantitative skin color measurements in acanthosis nigricans patients: colorimetry and diffuse reflectance spectroscopy

2012 ◽  
Vol 28 (4) ◽  
pp. 213-215 ◽  
Author(s):  
Bensachee Pattamadilok ◽  
Suneetha Devpura ◽  
Zain U. Syed ◽  
Oma N. Agbai ◽  
Pranita Vemulapalli ◽  
...  
Keyword(s):  
Skin Color ◽  
Diffuse Reflectance ◽  
Acanthosis Nigricans ◽  
Diffuse Reflectance Spectroscopy ◽  
Reflectance Spectroscopy ◽  
Color Measurements

If Looks Could Kill

2020 ◽  
Vol 3 ◽  
pp. 81-84
Author(s):  
Karen Chan
Keyword(s):  
Skin Color ◽  
Daily Rhythm ◽  
Significant Rate ◽  
Chinese Canadian ◽  
First Time ◽  
The Way

For me, rhythm means having consistency. The piece highlights my own experience with the disruption of my daily rhythm due to COVID-19. The first half shows my routine and interactions prior to COVID-19 while the second half shows my experiences in the present day. Prior to the virus, I had a day to day routine that was filled with noise. Everyday moved quickly and I established a daily rhythm. However, when COVID-19 spread, it changed everything. I felt like I didn’t have a routine anymore because I wasn’t allowed to go anywhere. Time was moving much slower and worst of all, xenophobia was growing at a significant rate. As a Chinese Canadian, this was the first time I truly felt the weight of the color of my skin. COVID-19 changed the way that I consistently assumed that the color of my skin wasn’t something that strangers would significantly care about. However, as I got on a bus, I unintentionally scared a woman simply because of my skin color. From that point, I knew that xenophobia would affect the way people perceived me everyday. The woman was scared of the virus— which in turn was scared of me—and I was scared that she would thwart her anger towards me because I am Chinese. If looks could kill, then the woman and I ironically both feared each other. Now, due to COVID-19, I am adapting to a new routine. A routine where the color of skin rings louder than any other sound.

Prevalence and Risk Factors of Hepatitis C Virus (HCV) in Tehsil Batkhela District Malakand, KPK, Pakistan

2018 ◽  
Vol 9 (06) ◽  
pp. 20251-20256
Author(s):  
Mudassir Khan ◽  
Shahrukh Khan ◽  
Shohra Haider ◽  
Fazal Jalil ◽  
Muhsin Jamal ◽  
...  
Keyword(s):  
Risk Factors ◽  
Hepatitis C Virus ◽  
Hepatitis C ◽  
Skin Color ◽  
Significant Risk ◽  
Rapid Test ◽  
Prevalence Ratio ◽  
Hcv Infection ◽  
Hcv Rna ◽  
Common Symptom

Background: Prevalence of Hepatitis C viral infection and its major risk factors has been found out in population of Batkhela, Khyber Pakhtunkhwa, Pakistan by taking number of volunteers from the interested area. HCV prevalence has not been researched in recent time here in this area, so that’s why we contributed. Materials and Methods: Ab rapid test cassette serum/plasma (USA) kit has been used for the mentioned purpose following by ELISA and finally PCR to find out active infection of virus. ICT positive individuals were reconfirmed by ELISA and then ELISA positive samples were carefully investigated by RT-PCR for Hepatitis C Virus. Results: The study population was of 770 volunteers belonging to the mentioned area of research, 453 males and 317 females. The overall prevalence was found to be 5.32% of HCV in Batkhela. This prevalence ratio was 3.12% in males and 2.20 % in females. 3rd generation ELISA was used to refine ICT positive samples which showed that 37 of the ICT positive samples had antibodies detected by ELISA. To find out active HCV infection, ELISA positive samples were refined by real time PCR which showed 2.98% of prevalence of active HCV infection in Batkhela based on HCV RNA in their blood. Principle Conclusion: Overall prevalence was found 5.32%, contaminated reused syringes and blades at Barbour’s shop, blood transfusion, surgical operations and unhygienic food in stalls etc were found significant risk factors for acquiring HCV infection. Body weakness and pale yellow skin color was common symptom in HCV positive volunteers. Safe sexual activities, blood screening before donation and sterilizing surgical equipment’s can protect us from Hepatitis C Virus.

A Quantitative Analysis of Skin Color Using a Videomicroscope and a Computer.

1993 ◽  
Vol 55 (3) ◽  
pp. 468-475 ◽  
Author(s):  
Hirotsugu TAKIWAKI ◽  
Shiro SHIRAI ◽  
Masahiro UTSUNOMIYA ◽  
Yasumori WATANABE ◽  
Yoshiyuki KANNO
Keyword(s):  
Quantitative Analysis ◽  
Skin Color

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.

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