Human Color Research Articles

Human visual gamma for color stimuli.

Strong gamma-band oscillations in primate early visual cortex can be induced by homogeneous color surfaces (Peter et al., 2019; Shirhatti and Ray, 2018). Compared to other hues, particularly strong gamma oscillations have been reported for red stimuli. However, precortical color processing and the resultant strength of input to V1 have often not been fully controlled for. Therefore, stronger responses to red might be due to differences in V1 input strength. We presented stimuli that had equal luminance and cone contrast levels in a color coordinate system based on responses of the lateral geniculate nucleus, the main input source for area V1. With these stimuli, we recorded magnetoencephalography in 30 human participants. We found gamma oscillations in early visual cortex which, contrary to previous reports, did not differ between red and green stimuli of equal L-M cone contrast. Notably, blue stimuli with contrast exclusively on the S-cone axis induced very weak gamma responses, as well as smaller event-related fields and poorer change-detection performance. The strength of human color gamma responses for stimuli on the L-M axis could be well explained by L-M cone contrast and did not show a clear red bias when L-M cone contrast was properly equalized.

The Eumelanin Human Skin Colour Scale: a proof-of-concept study.

At present there is no standard nomenclature for describing the diversity of human constitutive skin colour. To develop a standard nomenclature to describe human constitutive skin colour. Monthly focus group discussions were carried out among a multidisciplinary group of specialists over a 7-month period. Topics covered were (i) limitations and unmet needs of current nomenclature(s) pertaining to human cutaneous diversity, (ii) practical considerations about the function and role of any proposed nomenclature pertaining to human cutaneous diversity, (iii) review of the cellular basis and current molecular genetic understanding of variation in human skin pigmentation and (iv) in vivo methods to evaluate human skin pigmentation. In addition, a preliminary review of the published literature was undertaken to collate data on published skin reflectance measurements, notably melanin index values for well-referenced human populations. We developed a five-point scale to describe the full spectrum of human constitutive skin colour, termed the Eumelanin Human Skin Colour Scale. The nomenclature of the scale uses eumelanin, the dominant chromophore of human skin, as a central descriptive word. The categories of the scale (nomenclature and melanin index values) are eumelanin low (EML), < 25; eumelanin intermediate low (EMIL), 25 to < 50; eumelanin intermediate (EMI), 50 to < 75; eumelanin intermediate high (EMIH), 75 to < 100; and eumelanin high (EH), ≥ 100. The Eumelanin Human Skin Colour Scale enables the complete range of human constitutive skin colour to be described in an objective, equitable and understandable manner. In future, this scale can be used as the basis for developing other scales that address the specific functional aspects of human skin, such as response to ultraviolet radiation.

Books on Human Evolution

Books on Human Evolution

Perceptual hue, lightness, and chroma are represented in a multidimensional functional anatomical map in macaque V1.

Humans perceive millions of colors along three dimensions of color space: hue, lightness, and chroma. A major gap in knowledge is where the brain represents these specific dimensions in cortex, and how they relate to each other. Previous studies have shown that brain areas V4 and the posterior inferotemporal cortex (PIT) are central to computing color dimensions. To determine the contribution of V1 to setting up these downstream processing mechanisms, we studied cortical color responses in macaques-who share color vision mechanisms with humans. We used two-photon calcium imaging at both meso- and micro-scales and found that hue and lightness are laid out in orthogonal directions on the cortical map, with chroma represented by the strength of neuronal responses, as previously shown in PIT. These findings suggest that the earliest cortical stages of vision determine the three primary dimensions of human color perception.

Genetic diversity of the melanocortin-1 receptor in an admixed population of Rio de Janeiro: Structural and functional impacts of Cys35Tyr variant.

The melanocortin-1 receptor (MC1R) is one of the key proteins involved in the regulation of melanin production and several polymorphisms have been associated with different phenotypes of skin and hair color in human and nonhuman species. Most of the knowledge is centered on more homogeneous populations and studies involving an admixed group of people should be encouraged due to the great importance of understanding the human color variation. This work evaluates the MC1R diversity and the possible impacts of MC1R variants in an admixed sample population of Rio de Janeiro, Brazil, which is a product of Native American, African, and European miscegenation. Sequencing of complete coding region and part of the 3´UTR of MC1R gene identified 31 variants including one insertion and three novel synonymous substitutions in sample population grouped according to skin, hair and eye pigmentation levels. In nonmetric multidimensional scaling analysis (NMDS), three main clusters were identified, in which the Brazilian dark skin group remained in the African cluster whereas the intermediate and the light skin color phenotype in the European one. None gathered with Asians since their immigration to Brazil was a recent event. In silico analyses demonstrated that Cys35Tyr, Ile155Thr and Pro256Ser, found in our population, have a negative effect on receptor function probably due to changes on the receptor structure. Notably, Cys35Tyr mutation could potentially impair agonist binding. Altogether, this work contributes to the understanding of the genetic background of color variation on an admixed population and gives insights into the damaging effects of MC1R variants.

Soft Biometrics Authentication

This manuscript presents the design of a new approach of human skin color authentication. Skin color is one of the most popular soft biometric modalities. Since a soft biometric modality alone cannot reliably authenticate an individual, this new system is designed to combine skin color results with other pure biometric modalities to increase recognition performance. In the classification process, we first perform facial skin detection by segmentation using the thresholding method in the HSV color space. Then, the K-means algorithm of the clustering method is used to determine the dominant colors on the skin pixels in the RGB model. Variations according to the R, G and B components are recorded in a reference model to enable an individual’s identity to be predicted on the basis of 30 clusters. Experimental results are promising and give a false acceptance rate (FAR) of 29.47% and a false rejection rate (FRR) of 70.53%.

You Can’t Hide Your Lying Eyes: Honesty Oaths and Misrepresentation

Lying about race or personal characteristics for a job or in college admissions is common and has recently become a high profile issue. In this paper, we explore the decision to misrepresent oneself and determine how honesty oaths impact personal characteristic reporting. To do this, we execute an experiment on Amazon MTurk, using a self-reporting task involving human eye color. We find that honesty oaths elicit more truthful behavior – primarily reducing implausible lies (maximal outcome lies). As a result, we spent 27.6% less on bonuses than we would have without oath-taking. There is some evidence that if one believes lying is common, they are more likely to lie as well. We conclude that oaths decrease extreme misrepresentation and expectations of group behavior significantly impact the decision to deceive.

The role of detectability in the evolution of avian-dispersed fruit color

If the primary function of avian-dispersed fruit coloration were the maximization of detectability, then the commonest avian-dispersed fruit colors should be the ones most detectable to birds. We tested this prediction by photographing 63 fruit species primarily dispersed by birds, in situ in Sweden and Australia, with a multispectral camera closely mimicking the predominant spectral sensitivities of birds, including both UVS and VS (peak ultraviolet sensitivity ∼370 and 409 nm respectively) visual systems. Fruits were classified into nine distinct color categories based on different patterns of cone excitations, and were named by combining human color names with fruits’ UV reflective properties. For example, a bluish-UV fruit would be a fruit that excited the avian UV cone the most, but that also strongly excited the blue cone. Color and achromatic contrasts were calculated between each fruit color and common background objects, and compared to the relative abundance of the different fruit colors. Although red was highly detectable and the commonest color, the second and third commonest colors, purplish-UV and bluish-UV (often termed “black” by humans), were the least detectable. Although these latter two colors were more detectable to UVS than to VS birds, they were the least detectable to both visual systems. Rare fruit colors, such as UVish-purple, pink, and orange, were highly detectable to both visual systems. The lack of correlation between fruit color abundance and detectability suggests that the maximization of detectability has not been the primary driving force behind the evolution of fruit color.

Research Into Monochromatic Colour Vision Thresholds And Determination Of The Trichromatic ColourMatching Coefficients

The authors experimentally defined the dependences of chromaticity thresholds between an object and a background for 10 trichromatic observers. The experiments included observation of monochromatic objects with dimension of (2?2) angular degree against a white background. Based on the statistical theory of human threshold colour vision, it was proved that in the XYZ colorimetric system, the value of Y coordinate of the primary colour Mphys is positive and lies along the y=1x line. This fact allowed to define all the characteristics of a trichromatic physiological system (LMS)phys necessary for chromatic calculations.

Deep neural models for color classification and color constancy.

Color constancy is our ability to perceive constant colors across varying illuminations. Here, we trained deep neural networks to be color constant and evaluated their performance with varying cues. Inputs to the networks consisted of two-dimensional images of simulated cone excitations derived from three-dimensional (3D) rendered scenes of 2,115 different 3D shapes, with spectral reflectances of 1,600 different Munsell chips, illuminated under 278 different natural illuminations. The models were trained to classify the reflectance of the objects. Testing was done with four new illuminations with equally spaced CIEL*a*b* chromaticities, two along the daylight locus and two orthogonal to it. High levels of color constancy were achieved with different deep neural networks, and constancy was higher along the daylight locus. When gradually removing cues from the scene, constancy decreased. Both ResNets and classical ConvNets of varying degrees of complexity performed well. However, DeepCC, our simplest sequential convolutional network, represented colors along the three color dimensions of human color vision, while ResNets showed a more complex representation.

THE TWO SINGLE NUCLEOTIDE POLYMORPHISM HAPLOTYPES ON CHROMOSOME 15 OF THE HERC2 AND OCA2 GENES OF THE COLOR VARIATION OF THE HUMAN EYE IN A SAMPLE OF IRAQI POPULATION

This study was aimed to identify the role of the single nucleotide polymorphism genes on the contrast of three groups (Dark-Brown, hazel and blue) of human eye color among a sample of Iraqi people specifically single nucleotide polymorphism (SNPs); the rs12913832 of HERC2 gene and the rs1800407 of OCA2 gene, for 90 human blood samples of different people were collected from College of Science, University of Baghdad and also people from different areas of Baghdad, Iraq. These SNPs were analyzed using quantitative real-time PCR (qPCR). The results of the rs12913832 and rs1800407 genotype showed significant differences (p &lt;0.05) in the blue eye color groups. the rs12913832 of HERC2; rs1800407 of the OCA2 genotypes and allele frequencies in contrast to the dark brown and blue iris group showed that there was significant variation in the heterozygous genotype frequencies, while these SNPs in contrast to the dark brown and hazel iris group showed a non-significant effect in a sample of Iraqi population. The haplotype statistical analysis shows strongly Linkage disequilibrium (LD) between the rs12913832 of HERC2 gene and the rs1800407 of OCA2 gene in dark-brown, hazel and blue eye color subjects.

From Human’s Attitude Towards Scars to Innovative Bio Textile Substitute Derived from Soil to Create Garments for the Future

The objective of this research article is to study and carry out research in the biological innovation of the substitute textile derived from soil and through series of improved material efficiency, and we were able to produce future costume prototype that have been resulted from the 3 elements of conceptual framework. The 3 elements are firstly to create innovation based on scientific knowledge through the use of synthetic bio fiber processing and synthetic brown pigmentation that resemble melanin cell in human skin according to research in the skin of the Thai population. Secondly, it is to add value to the natural resource base which focuses on a circular production process that is environmentally friendly. Lastly, it is to exhibit the empirical design aesthetic through using the substitute textile that resembles the human skin color. If one is taking a closer look at the substitute textile, one would consider it to be wounds or operation scars. These permanent marks or scars are either the evidence of sadness and embarrassment feelings or the safety and survival. The researcher has applied this concept into clothing design by using substitute textile produced from soil. This new form of textile is meant to portray the true meaning of beauty caused by imperfections. These imperfections are the symbol of life, expressing the communication of rounds of existence between nature and human.

Human perception of color differences using computer vision system measurements of raw pork loin

In the food industry, product color plays an important role in influencing consumer choices. Yet, there remains little research on the human ability to perceive differences in product color; therefore, preference testing is subjective rather than based on quantitative colors. Using a de-centralized computer-aided systematic discrimination testing method, we ascertain consumers' ability to discern between systematically varied colors. As a case study, the colors represent the color variability of fresh pork as measured by a computer vision system. Our results indicate that a total color difference (ΔE) of approximately 1 is discriminable by consumers. Furthermore, we ascertain that a change in color along the b*-axis (yellowness) in CIELAB color space is most discernable, followed by the a*-axis (redness) and then the L*-axis (lightness). As developed, our web-based discrimination testing approach allows for large scale evaluation of human color perception, while these quantitative findings on meat color discrimination are of value for future research on consumer preferences of meat color and beyond.

A Hybrid Clustering-Based Approach to Color Modification of Art Paintings for Protanopes and Deuteranopes

The normal human color vision is trichromatic, and it originates from the comparison of the rates at which photons are absorbed by three types of photoreceptor cone-cells contained in the eye's retina. The absence or malfunctioning of one or two types of cone results in color-blindness. This paper proposes an algorithmic framework to appropriately modify (i.e., recolor) art paintings for two types of color-blindness called protanopia and deuteranopia. The algorithmic framework employs four distinct steps applied in sequence. First, the image colors are clustered into a prespecified number of representative colors. The second step determines the representative colors that are confused by the protanopes or the deuteranopes. Third, an optimization problem is proposed to appropriately recolor the representative colors detected in the previous step. Finally, given the recolored representative colors, the original image pixels associated with those colors are also modified accordingly. The method is tested and evaluated in terms of quantitative, qualitative, and subjective comparison with three other recoloring algorithms. The results are promising in the sense that the proposed method outperforms the competitive algorithms, maintaining the overall aesthetic of the paintings.

Evaluation of native canine skin color by smartphone-based dermatoscopy.

Human skin color, predominantly determined by the chromophores of melanin, hemoglobin, and exogenous carotenoids, is often measured to serve various medical and cosmetic applications. Although colorimetry has been used to evaluate the skin erythema in allergic dogs, the native canine skin color remains unknown. We measured the skin color in 101 healthy dogs using a calibrated optical system with a smartphone and a mobile dermatoscope DermLite DL1. The results were retrieved in the CIELAB color system and compared to the human color ranges. The lightness (L*) of canine skin ranged from 28.5 to 78.3, which is slightly broader than that of human skin. There was a difference of 3.9 in redness (a*) between canine and human skin, but this variation could be attributed to the similarly valued colorimetric error of the optical system. Nonetheless, the skin yellowness was significantly different for dogs and humans (respective median b* of 12.3 versus 16.6, p<0.01). This difference might be due to canids not being able to accumulate typically yellowish carotenoids. Furthermore, the native canine skin color did not exhibit a typical dependence between the coordinates of lightness (L*) and yellowness (b*), known as the individual typology angle, °ITA. We reported the first dataset of the native canine skin color in the CIELAB color space. We discovered a similarity in skin lightness and a difference in skin yellowness. However, further studies are needed for a more precise comparison of skin redness.

Development of telemedicine tools with an emphasis on visual observation.

We developed a system to improve the quality of telemedicine, and the test results obtained have been presented in this paper, along with the technical details of the system. The spread of COVID-19 has accelerated the need for telemedicine to effectively prevent infections. However, in traditional Japanese medicine (Kampo), where color is essential, an accurate diagnosis cannot be made without color reproduction. Because commercial smartphones cannot reproduce colors with the level of fidelity required for medical treatments, we created a color chart that includes the human skin and tongue colors to help doctors identify their colors accurately during a telemedicine examination. Further, we developed a telemedicine system that allows for automatic color correction using a mobile device, with a color chart and non-contact heart rate measurements.

Color image perception based on stochastic spiking neural network

Our aim is to present an interpretable algorithm for enhancing low-illuminance color image based on the principle of stochastic resonance and the fundamental biophysical process of human brain perceiving object color. To this end, the phenomenon of stochastic resonance in a conductance-based integrate-and-fire neuronal network is first explored, with the effect of firing threshold, synaptic weight and the population size on the signal-to-noise ratio revealed, and the firing threshold is recognized as the key parameter for the resonance effects. And then, a color image enhancement algorithm, where the peak signal-to-noise ratio and the natural image quality evaluator are adopted as quantifying indexes, is developed by combining the stochastic spiking neuronal network and the involved biophysical process relating to visual perception. Note that the enhanced image is aperiodic, thus in order to optimize the performance of the algorithm, an illuminance distribution based threshold strategy is given by us for the first time. The numerical tests show that the algorithm has good enhancement performance and stability. We wish this algorithm could be applied to relevant signal processing fields such as military detection and medical image preprocessing.

Ultrasound phantom with solids mimicking cancerous tissue for needle breast biopsy.

This study aimed at synthesizing hydrogels to simulate opaque breast tissue (BT) and coloured cancerous tissues (CT) at different densities of the designed phantom to improve the biopsy-related skills along with ultrasonography. Both tissues are tear-resistant and therefore, the phantom can be trained multiple times in order to lower the price and improve the eye-hand coordination of users. For this purpose, self-healing (SH) polyacrylamide (PAAm) hydrogels (SH hydrogel) obtained by free-radical polymerization of AAm, in the presence of chemical cross-linker, BAAm, physical cross-linker stearyl methacrylate, C18, and ammonium persulfate APS as initiator were used in the design of phantoms. Psyllium was added to the BT to differentiate density and obtain human skin color and it could be distinguished from the CT which was also colored with methyl violet. BT and CTs were characterized with FTIR spectroscopy, mechanical, swelling, and refractive index measurements. Designing phantoms from BT and CT were characterized by ultrasonography, mechanical tests, observation of needle track after biopsy, and stabilization tests to follow the self-healing behaviours of tissues with time. As a result of this study, self-healing, low-cost, and suitable for multi-usage ultrasonographic phantom for needle breast biopsy was designed and cancerous tissue was successfully detected.

Insights of Handloom Producers of Sirajganj District in Bangladesh

This study was undertaken to measure the current socioeconomic and profitability status of the traditional handloom producers living in Sirajganj district of Bangladesh. Primary data were collected from 60 randomly selected handloom owners. Two main products were considered in this study, i.e., sharee and gamcha . Descriptive statistics and cost-return analysis were performed to assess the present situation and profitability of handloom production. The Gini Coefficient and Lorenz Curve measured inequality among respondents. A log transformed multiple linear regression model was applied to explore the factors influencing handloom products production. Results revealed that most of the handloom weaving was financed through the weavers’ own capital and taking loans from the bank. The undiscounted benefit-cost ratios were 1.12 and 1.20 for sharee and gamcha, respectively, indicating both enterprises were profitable but gamcha was more profitable than sharee. The Gini Coefficient of handloom weavers’ income is less than 0.25. Results from the regression analysis revealed that human labour, yarn, color, and processing cost significantly impacted sharee and gamcha production. Therefore, efficient utilization of these resources in the production process of handloom products would be essential that can bring more profit for handloom production.

Euclidean Distance Versus Manhattan Distance for New Representative SFA Skin Samples for Human Skin Segmentation

The human color skin image database called SFA, specifically designed to assist research in the area of face recognition, constitutes a very important means particularly for the challenging task of skin detection. It has showed high performances comparing to other existing databases. SFA database provides multiple skin and non-skin samples, which in various combinations with each other allow creating new samples that could be useful and more effective. This particular aspect will be investigated, in the present paper, by creating four new representative skin samples according to the four rules of minimum, maximum, mean and median. The obtained samples will be exploited for the purpose of skin segmentation on the basis of the well-known Euclidean and Manhattan distance metrics. Thereafter, performances of the new representative skin samples versus performances of those skin samples, originally provided by SFA, will be illustrated. Simulation results in both SFA and UTD (University of Texas at Dallas) color face databases indicate that detection rates higher than 92% can be achieved with either measure.