Hue Saturation Brightness Research Articles

THE PALETTE OF COLORS IN THE AUTUMN LANDSCAPE OF ROMANESCU PARK

This study explores the influence of autumn colors on the aesthetic and emotional impact of the landscape in Nicolae Romanescu Park, Craiova, Romania. Using digital photography and Adobe Photoshop, a color palette was generated to analyze the hue, saturation, brightness (HSB), and CIELab* parameters of the vegetation. Results show that the autumn palette is dominated by green and yellow hues, with a visible gradient in leaf colors reflecting seasonal changes. Warm colors provide visual energy and create a sense of movement, while green tones maintain balance and tranquility. These findings demonstrate how color can shape the aesthetic appeal of landscapes and affect the emotional well-being of visitors.

An investigation into the relationship between clothing colors and gender stereotyping in children

This paper investigates the relationship between children's clothing color and gender stereotyping, as well as the underlying mechanisms. Sample colors were chosen based on their representativeness and prevalence, and characterized using the HSB (Hue-Saturation-Brightness) color model. Through sensory experiments, it is found that most colors have varying degrees of gender association. The paper explores the general principle of how gender stereotyping is induced from the perspective of the CMY color theory and analyzes the relationship between color brightness, saturation, and gender stereotyping by establishing regressional models. It is also found that the formation of gender stereotypes in children's clothing is related to people's different expectations for the temperament and behavior patterns of children of different genders through perceptual experiments. Understanding the gender tendencies conveyed by colors can offer designers guidance in the application of colors when creating products targeted at specific markets characterized by different gender cognitive inclinations. Besides, the findings of the study will inform future research in the fields of clothing psychology and children's gender cognition education.

A spatial color co-recognition immunochromatographic assay based on the hue-saturation-brightness color space to classify Salmonella serogroups

Salmonella causes a huge proportion of foodborne diseases worldwide. There are over 2650 serotypes of Salmonella isolates with varying virulence and pathogenicity, while the serotype classification of Salmonella by traditional slide agglutination tests is time-consuming and tedious. Multiple immunochromatographic assays can distinguish multiple targets simultaneously in high throughput but are often limited to the visually confusing interpretation of the results. Herein, we established a spatial color co-recognition immunochromatographic assay based on the hue-saturation-brightness (HSB) color space to classify the 4 most common Salmonella serogroups (O:2, O:3, O:7, and O:9). The HSB color space was introduced to interpret the multicolor results of the strips. Thus, the four Salmonella serogroups could be classified clearly by one single test in the assay. The sensitivity and specificity of the spatial color co-recognition immunochromatographic assay for the four serogroups were both 100 %. An android app based on the HSB color space was also developed to interpret the test strip results. Compared to the common red-green-blue (RGB) color space, the HSB color space demonstrates better performance in the recognition of multicolor immunochromatographic strips. This study provides a novel and stable result interpretation assay for multicolor immunochromatographic assays and provides a fast and accurate classification method for Salmonella serogroups.

Diagnosis of lameness via data mining algorithm by using thermal camera and image processing method in Brown Swiss cows.

Lameness is one of the culling factors such as mastitis, low milk yield, and infertility that cause economic losses in herd management as they threaten animal health and welfare. The purpose of this study was to evaluate the early detection of lameness in Brown Swiss cattle by using a data mining algorithm by both integrating lameness scores and some image parameters such as Lab (CIE L*, a*, b*), HSB (hue, saturation, brightness), RGB (red, green, blue) by processing thermal images with ImageJ program. In the study, the variables obtained as a result of processing the skin surface temperatures and thermal images taken at the fetlock joint of 33 Brown Swiss cattle were used as independent variables. Also, healthy cows (lameness scores 1 and 2) and unhealthy cows (lameness scores 3, 4, and 5) used in the diagnosis of lameness were used as a binary response variable. Classification and regression tree (CART) was used as a data mining algorithm in the diagnosis of lameness. As a result, the CART algorithm correctly classified 12 of the 13 heads unhealthy cows according to locomotion scores. According to locomotion scores by using CART analysis in this study, independent variables that are used to classify healthy and unhealthy (lame) animals were determined as maximum temperature (Tmax), green (mean), L (max), and age (P<0.05). The cut-off values of these independent variables were predicted as 32.40, 149.14, 97.11, and 5.50 for Tmax, green (mean), L (max), and age, respectively. Also, the sensitivity, specificity, and area under the ROC curve (AUC) of the CART algorithm for locomotion scoring were found as 92.31%, 95%, and 93.7% respectively. The area under ROC curve (AUC) was found to be significant in the diagnosis of lameness (P<0.01). Results showed that the use of CART classification algorithm together with thermal camera and image processing methods is a usefull tool in the detection of lameness in the herds. It is recommended that more comprehensive studies by increasing the number of animals in the future would be more beneficial.

Leaf color attributes of urban colored-leaf plants

Abstract Plant color was an important landscape of the urban green space, and quantitative analysis of its characteristics could provide a basis for plant color configuration. The leaf color attributes of 80 colored-leaf plants were studied and the Scenic Beauty Estimates (SBE) was used to evaluate their beauty. The data of leaves color were obtained by MATLAB software and scanner under the hue–saturation–brightness (HSB) system and then were further analyzed to determine the relationship between the SBE and color attributes (HSB). Results showed that the leaf colors of 80 plants contained 13 hues in total, which belonged to six color systems. The species contained in different color systems, from most to least, were yellow–green series (27 species) &gt; orange series (19 species) &gt; red series (18 species) &gt; yellow series (10 species) &gt; blue-green (four species) &gt; purple (two species). There were fewer blue and purple series species. The brightness and saturation of color were mainly distributed in the middle (26–50%), middle and high (51–75%) stages, and those of the yellow–green system belonged to the medium and high stages and were significantly higher than other color systems. There is a significant positive correlation between the brightness and saturation of color and the value of SBE, and an SBE evaluation model was established based on the color attributes. The results are helpful to select plants with higher beauty and create a rich plant color landscape.

Pretrained DcAlexnet Cardiac Diseases Classification on Cognitive Multi-Lead Ultrasound Dataset

The DcAlexNetCNN deep learning classifier can easily track patterns in medical images (brain, heart, spinal cord and etc.) precisely. According to WHO (world health organization) every year 5 billion people are affecting heart diseases and heart-attacks. Heart abnormalities sometimes tends to death; therefore, an efficient medical image pre-processor and deep learning classifier is needed for diagnosis. So that in this research work multi-class DcAlexNet classifier, RRS-HSB segment-filter has been implemented. The RRS (Restrictive Random segmentation) and GHSB (Gaussian Hue saturation brightness filtration) modules are fused to get multi-level feature. The training process has been incorporated to EchoNet dataset and testing process can be verified to real time samples. The segmented features as well as filtered feature are loaded into weighted .CSV file. The following features are classified tends to get predicting abnormalities in heart ultra sound image. The pretrained DcAlexNet CNN model is loading to EchoNet 1 lakh samples using 165 layers such as normalized layer, dense layer, flatten layer, max pooling layer and ReLu layer. The computer aided design with corresponding CNN layers has been finding hidden sample over to get heart abnormality location. The experimental results in terms of Dice score 98.89%, Accuracy 99.455, precision 99.23%, recall 98.34%, F-1 score 98.92%, CC 99.27%, and sensitivity 99.34% had been attained. The attained performance metrics are competed with present technologies and outperformance the application accuracy on heart diagnosis.

Virtual reconstruction of the painting process and original colors of a color-changed Northern Wei Dynasty mural in Cave 254 of the Mogao Grottoes

The Northern Wei Dynasty (386–534 CE) murals of Cave 254 in the Mogao Grottoes, China, have been extensively affected by pigment color changes and fading. These issues severely hinder efforts to correctly understand the value and painting process of murals from this historic period. The virtual reconstruction of the faded murals reflects the analysis results of the pigments applied during the painting process and provides a new direction for conservation and art research. However, simple virtual reconstructions may not be accurate owing to deficiencies in our understanding of the color-changed pigments and fading of image lines. In this study, multi-band imaging (MSI) was performed to obtain infrared-reflected false color, ultraviolet-reflected false color, and ultraviolet luminescence images of the mural. A portable X-ray fluorescence spectrometer, portable digital microscope, scanning electron microscope, energy dispersive X-ray spectrometer, liquid chromatography–mass spectrometer, and confocal Raman microscope were used. Non-invasive and minimally invasive analyses of local portions of different color areas were performed to identify their pigments and map the strata, and a hue–saturation–brightness palette was constructed for these pigments. Finally, the pigment analysis results were combined with the multi-band image features to determine the pigment distribution of the mural, which was then used to virtually reconstruct the original color and appearance of the faded mural under ideal conditions. This study is the first to use a virtual reconstruction based on objective analyses to simulate the original color, painting processes, and pigment stratigraphy of a mural from the Northern Wei Dynasty. A preliminary discussion of the relationship between the painting processes of the mural and color changes in its pigments was also performed. The findings of this study will provide new perspectives on the study of Northern Wei Dynasty murals.

Potassium Sulfate Spray Promotes Fruit Color Preference via Regulation of Pigment Profile in Litchi Pericarp.

Fruit color is a decisive factor in consumers’ preference. The bright red color of litchi fruit is associated with its high anthocyanin; however, poor fruit coloration is a major obstacle in litchi plantation. The role of spraying mineral nutrient salts such as KH2PO4, KCl, K2SO4, and MgSO4 on litchi pericarp pigmentation was examined by a field trial, and the relation between human visual color preference versus pericarp pigments and hue-saturation-brightness (HSB) color parameters was investigated. K2SO4-sprayed litchi fruit gained the maximum popularity for its attractive red color. Spray of K and Mg salts decreased the buildup of yellowish pigments, but increased the accumulation of red ones, with the exception of slightly reduced anthocyanins in KH2PO4-sprayed fruit, by regulating the activities of enzymes involved in anthocyanidin metabolism and decreasing pericarp pH, leading to varied pericarp pigment composition. K2SO4 spray generated the highest percentage of cyanidin-3-glucoside over all pigments in pericarp. Correlation analysis shows the percent of cyanidin-3-glucoside, superior to anthocyanin concentration and HSB color parameters, was a reliable indicator to fruit color preference. This work demonstrates that spray of suitable mineral salt can regulate pericarp pigment profile, and is an effective approach to improve fruit pigmentation and promote its popularity.

A smart large-scale explosive-responsive amorphous photonic crystal sensor based on color analysis method

Leveraging advances in nanoscience and intelligent technology to engineer large-scale and stimuli-response amorphous photonic crystals (APCs) for use in inexpensive and portable sensing system for the detection of explosives. Polymethyl methacrylate (PMMA) colloidal microspheres with uniform particle size and good mono-dispersion were used to prepare APCs by spraying method. The structural color of APCs was angle-independent and changed with different microspheres size. Meanwhile, a robotic arm was designed to achieve an automatic and large-scale preparation of APCs, and this more accurate and cost-effective method not only provides an automatic process for large-scale APCs pattern painting in chemical industry, but also gives chemical sensors an access to be smart devices in life. Then 2,4,6-trinitrotoluene (TNT), 1,3,5-trinitro-1,3,5-triazacyclohexane (RDX) and cyclotetramethylenete-tranitramine (HMX) molecularly imprinted APCs (MIAPCs) were fabricated in the same way. The results showed that the response time of MIAPCs was 10 s, and the limit of detection was 0.01 mM with NaOH swollen. Specially, by using the more convenient HSB (Hue-Saturation-Brightness) and CIE (Commission Internationale de L’Eclairage) color analysis methods, combined with principal component analysis and pattern recognition methods, a sensor group with higher selectivity and sensitivity than a single sensor was constructed. A qualitative and semi-quantitative result was realized by responding to the changes of structural color before and after. Compared with traditional PhCs sensor, the APCs sensor has angle-independent structural color, which provides more accurate results and simplifies the detection based on the color analysis. This novel large-scale APCs sensor represents a potential of highly selective and real-time on-site visual explosive detection. In the meanwhile, the automatic APCs casting also offers chemical materials an access to combining with intelligent technology.

Selection of Image Texture Analysis and Color Model in the Advanced Image Processing of Thermal Images of Horses following Exercise

Simple SummaryDetecting horse state after exercise is critical for maximizing athletic performance. The horse’s response to fatigue includes exercise termination or exercise continuation at a lower intensity, which significantly limit the results achieved in races and equestrian competition. As conventional methods of detecting and quantifying exercise effort have shown some limitations, infrared thermography was proposed as a method of contactless detection of exercise effect. The promising correlation between body surface temperature and exercise-dependent blood biomarkers has been demonstrated. As the application of conventional thermography is limited by low specificity, advanced thermal image analysis was proposed here to visualize the link between blood biomarkers and texture of thermal images. Twelve horses underwent standardized exercise tests for six consecutive days, and both thermal images and blood samples were collected before and after each test. The images were analyzed using four color models (RGB, red-green-blue; YUV, brightness-UV-components; YIQ, brightness-IQ-components; HSB, hue-saturation-brightness) and eight texture-features approaches, including 88 features in total. In contrast to conventional temperature measures, as many as twelve texture features in two color models (RGB, YIQ) were linked with blood biomarker levels as part of the horse’s response to exercise.As the detection of horse state after exercise is constantly developing, a link between blood biomarkers and infrared thermography (IRT) was investigated using advanced image texture analysis. The aim of the study was to determine which combinations of RGB (red-green-blue), YUI (brightness-UV-components), YIQ (brightness-IQ-components), and HSB (hue-saturation-brightness) color models, components, and texture features are related to the blood biomarkers of exercise effect. Twelve Polish warmblood horses underwent standardized exercise tests for six consecutive days. Both thermal images and blood samples were collected before and after each test. All 144 obtained IRT images were analyzed independently for 12 color components in four color models using eight texture-feature approaches, including 88 features. The similarity between blood biomarker levels and texture features was determined using linear regression models. In the horses’ thoracolumbar region, 12 texture features (nine in RGB, one in YIQ, and two in HSB) were related to blood biomarkers. Variance, sum of squares, and sum of variance in the RGB were highly repeatable between image processing protocols. The combination of two approaches of image texture (histogram statistics and gray-level co-occurrence matrix) and two color models (RGB, YIQ), should be considered in the application of digital image processing of equine IRT.

Estimating Visible Band Albedo from Aerial Orthophotographs in Urban Areas

Albedo is an important parameter in many environmental and renewable energy models. Satellite sensors can be used to derive broadband or narrowband albedos. However, the spatial resolution of such data can be insufficient in urban areas with complex morphology and land cover diversity. In this study, we propose the use of widely available aerial orthophotographs to derive visible band albedo in urban surfaces that can be effectively used in high-resolution applications. The solution is based on the estimation of the reflected irradiance captured by an RGB sensor and approximated by the brightness component in the hue-saturation-brightness (HSB) color model and incident solar irradiance modelled by the r.sun module in GRASS GIS. The visible band albedo values are calibrated by published reference values for selected land cover classes or, alternatively, by a spectroradiometer. The method is applied to the central part of Košice and compared to visible band albedo derived from the Landsat 8 OLI and Sentinel 2A sensors and previously published typical albedo values for various land cover classes, resulting in reasonable agreement. The proposed methodology is implemented using standard GIS tools that are easily applicable to any high-resolution urban data.

Early Detection of Mastitis by using Infrared Thermography in Holstein-Friesian Dairy Cows via Classification and Regression Tree (CART) Analysis

Subclinical mastitis is an important udder disease that negatively affects both the animal health and reduces profitability in dairy farms. The increasing performance of thermal cameras over time and their usability in different areas increase their use in livestocks. Infrared thermography (IRT) technology is a noninvasive method that can estimate the surface temperature of objects. The objective of this study was to evaluate early detection of mastitis in Holstein-Friesian dairy cattle by using both udder surface temperatures (Tmax) from images obtained with the help of a FLIR One Pro thermal camera and some parameters such as Lab (CIE L*, a*, b*), HSB (Hue, Saturation, Brightness), RGB (Red, Green, Blue) by processing thermal images with the help of ImageJ program via classification and regression tree (CART) analysis. According to California Mastitis Test CMT by using CART analysis in this study, 64.9% of cows with udder surface temperature lower than 38.85 were healthy, and 73.3% of cows higher than 38.85 were determined as unhealthy. As for SCC, 77.6% of cows with udder surface temperature lower than 38.65 were healthy and 58.6% of cows with higher than 38.65 were determined as unhealthy. The areas under ROC (AUC) were found to be statistically significant in the diagnosis of subclinical mastitis. (P&lt;0.01) The sensitivity and specificity of the CART algorithm for CMT and SCC diagnostic tests were 85.42%, 81.48% and 90.20%, 80.39%, respectively. There was no significant difference between SCC and CMT tests in the area under the ROC curve (P&gt;0.05). As a result, IRT technology can be used as a useful diagnostic tool in the early detection of mastitis.

Commercially available color-catching sheets for magnetic textile solid phase extraction of water-soluble dyes

Magnetic textile solid phase extraction, based on the use of magnetically separable color-catching sheets, was successfully employed for the preconcentration of water-soluble dyes methylene blue and crystal violet from water solutions. The photos of color-catching sheet squares with the adsorbed dye were taken with a mobile phone. The computer-based image analysis of the photos was performed using ImageJ freeware while smartphone-based image analysis employed On Color Measure application. The values of saturation from HSB (hue – saturation – brightness) color space, as well as red channel values from RGB (red – green – blue) color space were proportional to the methylene blue and crystal violet concentration in the analyzed samples. This novel method has a potential to be a useful semiquantitative determination procedure for dye analysis.

Comparison of different mechanical traps to screening and control of whitefly (Aleyrodidea: Hemiptera) population in tomato crop

A significant issue is associated with the pest management control system and insect preferences for the tomato plants, Whiteflies masticate on the lower epidermis of the tomato plant leaves and eradicate tomato plants by diminishing the trim quality due to removal of the plant phloem, sucking out the sap, transmitting plant infections, and by discharging honeydew, which can increase leaf sheaths. Therefore, obstructing light absorption that results in less photosynthesis activity, causes the development of sooty mold. The adequacy of various sticky traps with various kinds of colors and cup traps against whitefly were assessed in tomato crops. The yellow sticky traps got whitefly adult an average of 374.2±48.65 during 24-h and 823.6±49.32 during 48h test periods per card. The wheat (fluorescent) sticky cards caught adult whitefly average of 391.4± during and 569.4±per card during a similar period. The Cup traps just got an average of 4.64±1.23 adult (Bemisia tabaci) over a 24-h and 7.28±1.12 in 48 h periods. Staying sticky traps got whitefly, sky blue or cyan (fluorescent) 299.4±49.08 and 488.9±87.34, somewhat bluish-green (fluorescent) 59±5.98 and 94.36±8.68, blue (fluorescent) 99.28±7.133 and 206.5±21.09 and red (fluorescent) 101±6.73 and 192.7±18.48, in 24h and 48h time frame individually. All traps caught other insects too. These outcomes exhibited those sticky traps with fluorescent colors more attractive and valuable to control whitefly (Bemisia tabaci) at other hand cup traps were helpful for monitoring. RGB (red, green, blue) and HSB (hue, saturation, brightness) value also estimate to check the correlation of color with whitefly. Both values showed a positive and in same negative correlation as well. Keywords: Sticky trap; Cup trap; Fluorescent; Mechanical; Bemisia tabaci; Whitefly http://dx.doi.org/10.19045/bspab.2020.90229

THE EFFECT OF ADDITION OF CANTHAXANTHIN IN FEED TO INCREASE THE VISUAL VIEW OF COMET FISH, Carassius auratus (Linnaeus, 1758)

One effort made to improve the color quality of comet fish is to add canthaxanthin. Canthaxanthin is a red-orange pigment found in plants, fungi, bacteria, crustaceans, sea trout, and algae. This study aims to determine the optimum dose of canthaxanthin given in feed to improve comet fish' color quality. This research is also expected to be beneficial for fish farmers related to the use of canthaxanthin to improve comet fish' color quality. This study used 5 treatments with 3 replications. This research was conducted in April-June 2019 at the Aquaculture Laboratory, Department of Fisheries and Marines, University of Lampung. The parameters observed were color measurement using the Red Blue Green (RGB) method, converted into the Hue Saturation Brightness (HSB) value, color measurement by the scoring method, and water quality. The addition of canthaxanthin in diets with different doses showed the highest results in treatment C (P &lt;0.05) on comet fish visual appearance. The results showed that the best dose in this study was the addition of canthaxanthin as much as 125 mg/kg of feed.

New Algorithm for Palm Print Detection

Advances in technology are increasing the demand for the biometric technology of palm print detection. This work presents a region of interest segmentation algorithm for palm prints based on Hue Saturation Brightness. The aim of this work was to detect palm print region of interest based on skin color and geometric features. After a color palm image is read as a JPEG file, the algorithm passes through three main stages of preprocessing: palm localization, region of interest localization and region of interest extraction. The preprocessing stage consists of three steps: conversion to Hue Saturation Brightness, skin color modeling, and de-noising. The second main stage of palm localization consists of clipping from the left, from the right, from the top and from bottom. The third stage consists of the two steps of determining and extracting region of interest. The algorithm was tested on a dataset of 180 palm images from the Institute of Automation Chinese Academy of Sciences dataset, which contains an equal number of right-hand and left-hand palm images. The results showed that the Hue Saturation Brightness color space for skin detection was superior to other recognition methods, with an accuracy rate of 98.8%.

Experimental Measurement Method for Contact Stress of Elastic Metal Sealing Ring Based on Pressure Sensitive Paper

As a basic mechanical component, the sealing ring is widely used in industrial, aerospatial, and other fields. In this study, an elastic metal C-shaped sealing ring with a wave structure was taken as an example, and its performance was analyzed theoretically and measured experimentally. First, an experimental study was performed on the C-ring seal. The proposed method for experimental measurement of the contact stress of the C-ring seal involved innovative use of a universal electronic testing machine and pressure sensitive paper, in conjunction with the hue–saturation–brightness (HSB) method. Based on the discoloration of the pressure sensitive paper after contact stress, computer software was used for analysis, the discoloration was digitized, and the contact stress was established. Second, a theoretical calculation model of the C-ring seal was established using ANSYS software, and a finite element theoretical calculation of the mechanical properties of the sealing ring was established. Finally, the contact stress results were compared with the model calculation results of the C-ring seal. The error between the two was small (4.8%), which proved the validity of the calculation model and the scientificity of the experimental method.

Pemodelan Antrian Sistem Pengambilan Pesanan Produk Pada Gudang Minuman Ringan Dengan Sistem Rak Drive-In

This paper proposed a queue model for beverage order picking system produced from agricultural commodity in warehouse with drive-in rack system in order to analyze and increase the warehouse performance. A (M/M/C):(GD/N/∞) queue approach was used to build the model with the queue approach. This paper considered total operator must-be-assigned to improve queue time (Wq), queue length, and utilization in the warehouse. Stack, queue, linked list, Colour HSB (Hue, Saturation, Brightness) algorithms were used to represent drive-in rack, product queuing, and product status in the warehouses. The model was implemented in computer simulation using java programming. After build the model, a real case industrial problem was presented to test the model. The model could calculate warehouse performance including low performance in racking, transportation to loading area, and loading process for current number of operators and idle operator in the warehouse process. This result was in line with the industry condition that has over capacity and high product bottlenecks in the warehouse. The model was used to find and analyze total operator-must-assigned to increase the warehouse performance. The computer simulation showed colour changing based on density of product stack in queue area. This colour degradation helped for easier understanding and accelerating product status detection (including hold, ready-to-release, and expired beverage products in the warehouse). Keywords:beverage warehousing, drive-in rack, order picking, queue modelling, queueing theory

A Case Report of Black Hairy Tongue Treated with Traditional Korean Medicine

Black hairy tongue is a benign medical condition, which is characterized by elongated filiform lingual papillae, with a typical carpet-like appearance on the dorsum of the tongue. We describe the case of a 70-year-old Korean female with black hairy tongue, who complained of black hairy tongue accompanied by xerostomia. The patient was treated with Jibaekjihwang-tang- gagambang and electric acupuncture for 13 days. Black hairy tongue was evaluated by its visual appearance and by calculating hue-saturation-brightness (HSB) and red-green-blue (RGB) values of images of the tongue using a photo-edit program. Salivary flow rate (SFR) was evaluated to evaluate oral dryness. After 13 days of treatment, the black fur disappeared, and the brightness and RGB values of the black fur increased. In addition, the SFR increased. We conclude that Korean medicine could be the treatment choice for black hairy tongue. Keywords: case report, black hairy tongue, xerostomia, herbal medicine, electric acupuncture, traditional Korean medicine

Development and evaluation of colour control interfaces for LED lighting.

To capitalise on the colour tuning capabilities of LED lighting, a model for converting device-specific control signals to chromaticity coordinates was used in a psychophysical experiment evaluating the usability of three colour control interfaces based on RGB (red, green, blue), HSB (hue, saturation, brightness) and opponent colour mixing systems. Although common and well accepted, the RGB interface had lowest usability based on both psychophysical results and subjective ratings. The usability of HSB and opponent colour interfaces was not significantly different. These findings can guide the development of useful and efficient colour control interfaces for tunable LED lighting systems.