Color Discrimination Research Articles

Color discrimination properties arising from optimal decoding in the early stages of visual systems

In order to interpret animal behavior we need to understand how they see the world. As directly testing color discrimination in animals is difficult and time consuming, it is important to develop theoretical models based in the properties of visual systems. One of the most successful for the prediction of color discrimination behavior is the receptor noise-limited (RNL) model, which depends only on the level of noise in photoreceptors and opponent mechanisms. Here a complementary approach to model construction is used, and optimal color discrimination properties are obtained using information theoretical tools, for the early stages of visual systems. It is shown here that, for most biologically relevant conditions the optimal discrimination function of an ideal observer coincides with the one obtained with the RNL model. Furthermore, within this framework the influence of opponency can be studied by considering models with and without that mechanism but with exactly the same parameters at the level of photoreceptors. As an example, it is shown here that opponency is necessary to explain the discrimination of monochromatic stimuli in honeybees, but not in budgerigars. Since this is a consequence of the narrowing of absorption spectra of photoreceptors, produced by the presence of oil droplets, this could also be true for most other species of birds. This suggests that in order to study opponency in birds, stimuli should have a relatively wide spectrum.

Color Inconstancy of Chromatic and Achromatic Textile Fabrics with Changes in the Correlated Color Temperature and Luminance of the Light Source

This study quantitatively analyzed how the color appearance of textile fabrics of varying lightness, chroma, and hue changes under a broad spectrum of illumination conditions. The color appearances of 203 chromatic (R, YR, Y, GY, G, BG, B, and RB) and achromatic fabrics were measured spectroradiometrically under 16 light sources with different correlated color temperatures (2700, 4000, 5000, and 6500 K) and luminances (50, 100, 500, and 1000 cd/m2). The color appearance values were compared with the spectrophotometrically measured physical color values of the fabrics, which were regarded as their true colors. The differences ranged up to 12.45 ∣ΔL*10∣, 19.32 ∣ΔC*ab,10∣, 161.83∣Δhab, 10∣, and 16.70 ΔECMC(2:1) units, which were significantly higher than the color discrimination thresholds of the human eye. Among 9 hue groups of fabrics, the color appearances of BG (bluish-green) fabrics were generally most affected by light sources, while those of achromatic fabrics were least affected with mean ΔECMC(2:1) of 6.32 and 1.03, respectively. It was also found that the correlated color temperature of light sources significantly affected all the lightness, colorfulness, and hue of fabrics, and the different trends of these effects were observed for different hue groups. Unlike current knowledge, light sources with a correlated color temperature of 6500 K did not always produce color appearances that most closely resemble the actual physical colors. Meanwhile, the luminance of light sources did not have a profound effect on the color appearances of fabrics.

Colour vision in the tropical giant mottled eel Anguilla marmorata as determined by classical conditioning test

The giant mottled eel Anguilla marmorata Quoy & Gaimard is an important aquaculture candidate in eel farming industry. The high economic value of the species leads to intensive cultivation affecting its welfare under farm condition. Since colour environment affects the welfare of confined fishes, basic information on colour vision is necessary. By means of a behavioural experiment of A. marmorata elvers in the laboratory, we determined colour vision under natural daylight. The elvers were subjected to classical conditioning to associate a reward feed with a blue or a green stimulus placed amid seven shades of grey. The elvers learned this visual task after 30 or 36 trials and thus the ability of colour discrimination was confirmed. Since the elvers have the retinal tapetum, it may be suggested that colour vision in dim light enables crepuscular feeding by the A. marmorata elvers, clearly an advantage in aquaculture.

Automated Operant Conditioning Devices for Fish. Do They Work?

Simple SummaryAutomated training devices are commonly used for investigating learning, memory, and other cognitive functions in warm-blood vertebrates, whereas manual training procedures are the standard in fish and other lower vertebrates, thus limiting comparison among species. Here, we directly compared the two different approaches to training in guppies (Poecilia reticulata) by administering numerical discrimination tasks of increasing difficulty. The automated device group showed a much lower performance compared to the traditionally-trained group. We modified some features of the automated device in order to improve its efficiency. Increasing the decision time or inter-trial interval was ineffective, while reducing the cognitive load and allowing subjects to reside in the test tank improved numerical performance. Yet, in no case did subjects match the performance of traditionally-trained subjects, suggesting that small teleosts may be limited in their capacity to cope with operant conditioning devices.The growing use of teleosts in comparative cognition and in neurobiological research has prompted many researchers to develop automated conditioning devices for fish. These techniques can make research less expensive and fully comparable with research on warm-blooded species, in which automated devices have been used for more than a century. Tested with a recently developed automated device, guppies (Poecilia reticulata) easily performed 80 reinforced trials per session, exceeding 80% accuracy in color or shape discrimination tasks after only 3–4 training session, though they exhibit unexpectedly poor performance in numerical discrimination tasks. As several pieces of evidence indicate, guppies possess excellent numerical abilities. In the first part of this study, we benchmarked the automated training device with a standard manual training procedure by administering the same set of tasks, which consisted of numerical discriminations of increasing difficulty. All manually-trained guppies quickly learned the easiest discriminations and a substantial percentage learned the more difficult ones, such as 4 vs. 5 items. No fish trained with the automated conditioning device reached the learning criterion for even the easiest discriminations. In the second part of the study, we introduced a series of modifications to the conditioning chamber and to the procedure in an attempt to improve its efficiency. Increasing the decision time, inter-trial interval, or visibility of the stimuli did not produce an appreciable improvement. Reducing the cognitive load of the task by training subjects first to use the device with shape and color discriminations, significantly improved their numerical performance. Allowing the subjects to reside in the test chamber, which likely reduced the amount of attentional resources subtracted to task execution, also led to an improvement, although in no case did subjects match the performance of fish trained with the standard procedure. Our results highlight limitations in the capacity of small laboratory teleosts to cope with operant conditioning automation that was not observed in laboratory mammals and birds and that currently prevent an easy and straightforward comparison with other vertebrates.

Relation between smoking and visual processing in bipolar disorder

Background: Although some studies have shown impairments in patients with bipolar disorder (BPD) and in smokers, it is unclear how these two factors work together. Our premise was that chronic smoking affects color discrimination and this is more pronounced in BPD. Objective: Our main purpose was to investigate the influence of smoking and BPD on color discrimination. Methods: Twenty-three smokers and 23 BPD smokers patients, aged 25–45 years old, participated in this study. Color vision testing was performed using the Trivector subtest of the Cambridge Colour Test. Participants’ task was to indicate the pseudoisochromatic stimulus in four directions (up, down, right, and left). Results: It was shown that the smokers had better color vision than BPD smokers for the Protan (p < .001), Deutan (p < .001), and Tritan (p < .001) (red, green, and blue, respectively) axes. Thus, the BPD smokers’ group had greater difficulty distinguishing the chromaticity variations (i.e., presented diffuse color vision impairments and not specific to any axis). Conclusions: The present study highlights a possible relationship between smoking and BPD in color discrimination. This highlights the importance of understanding the diffuse effects of this relationship.

Neural Mechanisms of Reward-by-Cueing Interactions: ERP Evidence.

Inhibition of return (IOR) refers to the phenomenon that a person is slower to respond to targets at a previously cued location. The present study aimed to explore whether target-reward association is subject to IOR, using event-related potentials (ERPs) to explore the underlying neural mechanism. Each participant performed a localization task and a color discrimination task in an exogenous cueing paradigm, with the targets presented in colors (green/red) previously associated with high- or low-reward probability. The results of both tasks revealed that the N1, Nd, and P3 components exhibited differential amplitudes between cued and uncued trials (i.e., IOR) under low reward, with the N1 and Nd amplitudes being enhanced for uncued trials compared to cued trials, and the P3 amplitude being enhanced for cued trials vs. uncued trials. Under high reward, however, no difference was found between the amplitudes on cued and uncued trials for any of the components. These findings demonstrate that targets that were previously associated with high reward can be resistant to IOR and the current results enrich the evidence for interactions between reward-association and attentional orientation in the cueing paradigm.

Color signals of bee-pollinated flowers: the significance of natural leaf background.

Flower color is a primary pollinator attractant and generally adjusted to the cognitive system of the pollinators. The perception of flower color depends on the visual system of pollinators and also on environmental factors such as light conditions and the background against which flowers are displayed. Using bee-pollinated Fabaceae species as a model, we analyzed flower color diversity and compared flower color signals considering both the standard green and the natural leaf background of two tropical seasonally dry vegetations-a mountain rupestrian grassland (campo rupestre) and a woody savanna (cerrado)-compared to a nontropical Mediterranean shrubland. By using natural background, bees discriminated color for 58% of the flowers in the campo rupestre and for only 43% in cerrado. Both vegetations were surpassed by 75% of bee color discrimination in Mediterranean vegetation. Chromatic contrast and purity were similar among the three vegetation types. Green contrast and brightness were similar between the tropical vegetations but differed from the Mediterranean shrubland. Green contrast differences were lost when using a standard green background, and most variables (purity, green contrast, and brightness) differed according to the background (natural or standard green) in all vegetations. The natural background influenced bee perception of flower color regardless of vegetation. The background of the campo rupestre promoted green contrast for flowers, ensuring flower detection by pollinators and, along with bees, may also act as a selective pressure driving the diversity of flower colors in Fabaceae species. We highlight the importance of considering the natural background coloration when analyzing flower color signals.

The evolution of opsin genes\xa0in five species of mirid bugs: duplication\xa0of long-wavelength opsins and loss\xa0of blue-sensitive opsins

BackgroundColor vision and phototactic behavior based on opsins are important for the fitness of insects because of their roles in foraging and mate choice. Related topics, including the duplication and loss of opsin genes, have been well investigated in insect orders such as Coleoptera, Lepidoptera, Hymenoptera, Odonata and Orthoptera, and the findings have been used to develop pest management strategies involving light trapping. Mirid bugs of Hemiptera, which are pests that cause heavy economic losses, show capacity for color discrimination and phototaxis. However, the opsins in mirid bugs remain uncharacterized. Herein, we examined five species to investigate the evolution of opsins in the family Miridae.ResultsUsing RNA-seq, we identified several contigs showing high identity with opsins, including four contigs in Apolygus lucorum and three contigs each in Adelphocoris suturalis, Adelphocoris fasciaticollis, Adelphocoris lineolatus and Nesidiocoris tenuis. Phylogenetic analyses indicated that one of these genes clustered with ultraviolet-sensitive (UV) opsins and that the others clustered with long-wavelength (LW) opsins, suggesting that duplication of LW opsins and loss of blue light-sensitive (B) opsins occurred in mirid bugs. The existence of introns in the LW opsins of mirid bugs suggested that the duplication events were DNA based. Both LW1 and LW2 opsins of mirid bugs were found to be under strong purifying selection. The LW1 opsins were significantly more highly expressed than the LW2 and UV opsins.ConclusionsWe identified the opsins of mirid bugs using five selected mirid species as a representative sample. Phylogenetic analyses clustered one of the genes with UV opsins and the others with LW opsins, suggesting the occurrence of LW opsin duplication and B opsin loss during the evolution of mirid bugs. Intron detection suggested that the identified duplication event was DNA based. The evidence of strong purifying selection and the relatively high expression levels suggested that these opsins exhibit fundamental functions in mirid bugs.

Neural correlates of visuospatial processing in migraine: does the pain network help?

Migraine patients frequently report cognitive symptoms during the different phases of migraine. The most affected cognitive domains are visuospatial abilities, processing speed, attention and executive functions. We explored migraine patients' performance during a visuospatial task and investigated the activity of brain areas involved in visuospatial processing. A functional magnetic resonance imaging (MRI) visuospatial task, including an angle and a colour discrimination paradigm, was administrated to 17 headache-free migraine patients and 16 controls. Correlations between functional MRI abnormalities and subjects' performance, clinical and neuropsychological variables were also investigated. Deficits at visuospatial cognitive tests were present in around 20% of patients. Migraine patients maintained a preserved behavioural performance (reaction time and number of correct responses) during the angle discrimination task, while they performed less correctly in the colour task compared to controls (p = 0.05).The comparison of angle vs. colour task revealed an increased activity of the right insula, bilateral orbitofrontal cortex and medial frontal gyrus, and decreased activity of the bilateral posterior cingulate cortex in migraine patients compared to controls. In migraine patients, a better performance in the angle task was associated with higher activation of the right insula and orbitofrontal cortex, as well as with decreased activation of the right posterior cingulate cortex. Our results suggest an adaptive functional plasticity that might help migraine patients to overcome impaired visuospatial skills and preserve an adequate performance during a visuospatial task. These compensatory mechanisms seem to take advantage of recruiting brain areas that are commonly involved also in nociception.

MicroRNA Signatures of the Developing Primate Fovea.

Rod and cone photoreceptors differ in their shape, photopigment expression, synaptic connection patterns, light sensitivity, and distribution across the retina. Although rods greatly outnumber cones, human vision is mostly dependent on cone photoreceptors since cones are essential for our sharp visual acuity and color discrimination. In humans and other primates, the fovea centralis (fovea), a specialized region of the central retina, contains the highest density of cones. Despite the vast importance of the fovea for human vision, the molecular mechanisms guiding the development of this region are largely unknown. MicroRNAs (miRNAs) are small post-transcriptional regulators known to orchestrate developmental transitions and cell fate specification in the retina. Here, we have characterized the transcriptional landscape of the developing rhesus monkey retina. Our data indicates that non-human primate fovea development is significantly accelerated compared to the equivalent retinal region at the other side of the optic nerve head, as described previously. Notably, we also identify several miRNAs differentially expressed in the presumptive fovea, including miR-15b-5p, miR-342-5p, miR-30b-5p, miR-103-3p, miR-93-5p as well as the miRNA cluster miR-183/-96/-182. Interestingly, miR-342-5p is enriched in the nasal primate retina and in the peripheral developing mouse retina, while miR-15b is enriched in the temporal primate retina and increases over time in the mouse retina in a central-to-periphery gradient. Together our data constitutes the first characterization of the developing rhesus monkey retinal miRNome and provides novel datasets to attain a more comprehensive understanding of foveal development.

Quantitative scoring methods of the Farnsworth D15 and Waggoner computerized D15 color vision tests in clinical practice

AbstractThe Farnsworth D15 (FR‐D15) color vision test is generally used to determine whether individuals with color vision defects have good color discrimination to perform their jobs safely. The Waggoner computerized color vision test D15 (WC‐D15) is a computerized version of the FR‐D15 test. This study aimed to evaluate the color differences vectors analyses (CDV) quantitative scoring in clinical practice using the FR‐D15 and WC‐D15 color vision tests. Fifty‐nine individuals with congenital red‐green color vision deficiency participated in this study. All participants were screened with the Ishihara, Waggoner Pseudoisochromatic plates, and City University Tests. Participants also completed FR‐D15 and WC‐D15 tests. The number of crossings, and CDV indices, including the confusion index, total error score, specificity index, and angle were assessed. There were significant correlations between the number of crossings and each of the CDV parameters. Results of both D15 tests showed that defects classified by confusion angles improve with an increase in crossings. The correct diagnosis rate improved when the criterion of failure was relaxed compared to the generally accepted criteria of ≥2. A CDV angle of either 0° or −3° accurately classifies defects as protan or deutan. Quantitative measurements of the FR‐D15 and WC‐D15 color vision tests showed good results in detecting color vision deficiency and diagnosing the type of defect. The CDV parameters positively correlated with the traditional evaluation of the defect's presence by counting the crossings. It is more accurate for clinicians to interpret their results using the CDV parameters.

HCHODetector: Formaldehyde concentration detection based on deep learning

Currently, deep learning technology is developing rapidly. Deep learning is mainly used in the fields of vision and hearing for human beings, but less in the field of olfactory. Formaldehyde is a common gas harmful to human health. However, the traditional methods of Formaldehyde concentration detection are inefficient in some cases. As for this problem, this paper proposes a novel formaldehyde detector namely HCHODetector. Specifically, this detector is based on deep learning and HSV colour space augmentation. Moreover, we propose a novel Mask-guided module and a novel pre-training network to enhance the colour discrimination ability of HCHODetector. As a consequence, the experimental results show that the detection error is within 0.08 mg/m3 in the actual environment, which provides a new idea for Formaldehyde concentration detection.

The Association of Visual Impairments of Elite Soccer Players with Concussion and Sports Injuries: A Prospective Cohort Study

Background: Visual skills play a pivotal role in athletic performance. However, in a professional setting, visual assessment is limited to a brief examination of visual acuity by the Snellen chart. This is while visual skills in sport comprise several other components. Objectives: This study aimed to evaluate the potential relationship between visual skills and sports injuries in professional soccer players. Methods: Through a prospective cohort study between September 2017 and October 2018, professional soccer league players were recruited for a complete eye examination including visual acuity, field of vision, and color discrimination as pre-competition examination. Any possible relationship between an abnormal eye finding and sports injury during the upcoming season was investigated. Results: A total of 386 male soccer players in 4 different playing positions were recruited from 16 league teams. Myopia, visual field defects, and green/blue/red color blindness were the most common visual impairments. Overall, there was no significant relationship between abnormal visual skills and the incidence of low back and upper extremity injuries among soccer players. However, a logistic regression model showed that the odds of quadriceps injury is 1.92 times higher (P-value: 0.005) for one diopter increase in both eyes' sum of refractive error. There is also an increased risk of concussion in players who have visual field defects (P-value &lt; 0.005). Conclusions: Visual field defects can put soccer players at a higher risk for concussion. Moreover, uncorrected refractive eye errors will increase the incidence of lower limb injuries, mostly quadriceps injuries.

Selective memory disrupted in intra-modal dual-task encoding conditions.

Given natural memory limitations, people can generally attend to and remember high-value over low-value information even when cognitive resources are depleted in older age and under divided attention during encoding, representing an important form of cognitive control. In the current study, we examined whether tasks requiring overlapping processing resources may impair the ability to selectively encode information in dual-task conditions. Participants in the divided-attention conditions of Experiment 1 completed auditory tone-distractor tasks that required them to discriminate between tones of different pitches (audio-nonspatial) or auditory channels (audio-spatial), while studying items in different locations in a grid (visual-spatial) differing in reward value. Results indicated that, while reducing overall memory accuracy, neither cross-modal auditory distractor task influenced participants' ability to selectively encode high-value items relative to a full attention condition, suggesting maintained cognitive control. Participants in Experiment 2 studied the same important visual-spatial information while completing demanding color (visual-nonspatial) or pattern (visual-spatial) discrimination tasks during study. While the cross-modal visual-nonspatial task did not influence memory selectivity, the intra-modal visual-spatial secondary task eliminated participants' sensitivity to item value. These results add novel evidence of conditions of impaired cognitive control, suggesting that the effectiveness of top-down, selective encoding processes is attenuated when concurrent tasks rely on overlapping processing resources.

Afro-descendant women Bolsa Familia and Supplemental Nutrition Assistance Program in Brazil and the United States

We examine the impact of class and racial discrimination on Afro-descendant women social welfare beneficiaries in Brazil and the USA. We focus on the cities Salvador, São Paulo, Charlotte, and Milwaukee. We find that in all these cities, more than a majority of social welfare beneficiaries ate dark skinned thus showing that both countries are pigmentocracies where disadvantage is based on skin color, class, and gender. We find that of those admitting they experienced skin color discrimination more than a majority ate dark skinned. Women in the USA are generally more likely to acknowledge skin color discrimination while women in Brazil are more likely to acknowledge class based discrimination.

Recent Advances in Perovskite Photodetectors for Image Sensing.

In recent years, metal halide perovskites have been widely investigated to fabricate photodetectors for image sensing due to the excellent photoelectric performance, tunable bandgap, and low-cost solution preparation process. In this review, a comprehensive overview of the recent advances in perovskite photodetectors for image sensing is provided. First, the key performance parameters and the basic device types of photodetectors are briefly introduced. Then, the recent developments of image sensors on the basis of different dimensional perovskite materials, including 0D, 1D, 2D, and 3D perovskite materials, are highlighted. Besides the device structures and photoelectric properties of perovskite image sensors, the preparation methods of perovskite photodetector arrays are also analyzed. Subsequently, the single-pixel imaging of perovskite photodetectors and the strategies to fabricate narrowband perovskite photodetectors for color discrimination are discussed. Finally, the potential challenges and possible solutions for the future development of perovskite image sensors are presented.

Weak Light-Stimulated Synaptic Hybrid Phototransistors Based on Islandlike Perovskite Films Prepared by Spin Coating.

An artificial synaptic device that can provide color discrimination, image storage, and image recognition is highly required to mimic the human vision for biological robots. All-inorganic halide perovskites have attracted extensive attention for the reason of their high stability and favorable photoelectric properties. In this study, a light-stimulated synaptic phototransistor based on a CsPbBr3/organic semiconductor hybrid film is reported. The fabricated CsPbBr3 film exhibits an island structure, which reduces the hysteresis effectively and at the same time achieves a high specific detectivity of up to 2 × 1015 Jones. The decay of the photocurrent can be delayed by changing the gate bias, which is essential for achieving high-performance light-stimulated synaptic devices. Due to the outstanding detectivity of the device, the obvious synaptic functions can be observed when triggered by a light signal with a power of 1.6 nW that is much weaker than previous most perovskite-based hybrid synaptic phototransistors under a low operating voltage of -1 V. The electrical power consumption of the device could be as low as 0.076 pJ when the power of light spike was 7.36 nW. Taking into account this characterization, with changing of light intensity or wavelength, the contrast of the image was enlarged, which can further promote the image recognition accuracy. More significantly, this CsPbBr3/TIPS hybrid film can be fabricated by facile and low-cost solution processes. This study indicates the great potential of solution-processed perovskite-based light-stimulated synapses for future artificial visual systems.

Comparison of colour difference formulas to best distinguish resected areas of malignant brain tumours from their background using 5-aminolevulinic acid fluorescence.

Fluorescence-guided surgery (FGS) with 5-aminolevulinic acid (5-ALA) has been proven to assist neurosurgeons to achieve a more complete brain tumour resection. However, 5-ALA-guided surgery is limited since it is often difficult to distinguish the colour difference between the resected areas of malignant brain tumours from their background. Our aim was to evaluate which colour difference formula was optimal to distinguish between malignant brain tumours and the background healthy tissue using 5-ALA fluorescence. Thirty-seven patients with a primary or secondary malignant brain tumour ingested 5-ALA before the surgery. A 400 nm light was used to excite the fluorescence. Surgical videos were recorded for all the patients and a total of 183 samples were obtained from the fluorescent areas and their respective backgrounds. Three colour differences formulas - contrast ratio (CR), CIELab (ΔE*) and CIEDE2000 - were applied to the videos and compared using hot-cold maps. Baseline demographics, the tumour's location, the tumour's side, and tumour's World Health Organization (WHO) grade was also analysed for correlations relating to the fluorescence. Chi-square and the Student's t-test were used for univariate relations. The three channels of the CIELAB colour space (L*, a* and b*) were analysed together and separately (since L* of fluorescent areas was significantly higher than the background). ΔE* resulted in good discrimination of a* and b*, and moderate but acceptable discrimination of L*. CIEDE2000 distinguished differences in a* and b*, although not in L*. The CR distinguished only L*, whereas the probability of discriminating a* and b* channels failed. Neither age, sex, tumour location, tumour size nor the WHO grade influenced the a*, b* and L* colour values (p > 0.05). Colour differences measured by ΔE* and CIEDE2000 correlated together (r = 0.99, p < 0.01), whereas CR correlated only with ΔE* (r = 0.21, p = 0.01) but not with CIEDE2000 (r = 0.07, p = 0.32). ΔE* obtained the best colour discrimination between the resected areas of malignant brain tumours and the background when compared to CR and CIEDE2000. Therefore, ΔE* may be the best formula to help neurosurgeons distinguish the colour differences when operating malignant brain tumours with 5-ALA fluorescence.

Pixel-Based Machine Learning and Image Reconstitution for Dot-ELISA Pathogen Diagnosis in Biological Samples.

Serological methods serve as a direct or indirect means of pathogen infection diagnosis in plant and animal species, including humans. Dot-ELISA (DE) is an inexpensive and sensitive, solid-state version of the microplate enzyme-linked immunosorbent assay, with a broad range of applications in epidemiology. Yet, its applicability is limited by uncertainties in the qualitative output of the assay due to overlapping dot colorations of positive and negative samples, stemming mainly from the inherent color discrimination thresholds of the human eye. Here, we report a novel approach for unambiguous DE output evaluation by applying machine learning-based pattern recognition of image pixels of the blot using an impartial predictive model rather than human judgment. Supervised machine learning was used to train a classifier algorithm through a built multivariate logistic regression model based on the RGB (“Red,” “Green,” “Blue”) pixel attributes of a scanned DE output of samples of known infection status to a model pathogen (Lettuce big-vein associated virus). Based on the trained and cross-validated algorithm, pixel probabilities of unknown samples could be predicted in scanned DE output images, which would then be reconstituted by pixels having probabilities above a cutoff. The cutoff may be selected at will to yield desirable false positive and false negative rates depending on the question at hand, thus allowing for proper dot classification of positive and negative samples and, hence, accurate diagnosis. Potential improvements and diagnostic applications of the proposed versatile method that translates unique pathogen antigens to the universal basic color language are discussed.

Prime Color Wavelengths Improve Color Discrimination

ABSTRACT Using comparative and iterative analyses of three-component spectral power distributions, this work demonstrates the advantage of locating radiation about the prime color wavelengths (near 450, 530, and 610 nm) over the anti-prime color wavelengths (near 490, 570, and 650 nm) for the purpose of maximizing color discrimination as measured by the Total Light Source Error Score, R d. To maximize color discrimination (minimize R d) most effectively in the design of a three-component spectrum, locate the primaries about the prime color wavelengths and increase their spectral width up to a full-width at half-maximum of 60 nm, at which R d is minimized. This work also details the internal logical consistency of quantifying color discrimination of a light source using R d, whereby the color discrimination ability of the daylight spectrum is set as ideal color discriminator meant to be replicated, not exceeded. Such internal logical consistency does not exist with quantifying color discrimination using gamut area, where is it demonstrably simple to exceed the performance of daylight (i.e., R g ≥ 100).