Color Quality Evaluation Research Articles

Perception and Acceptance of Shade Variances in the Smile.

(1) This study aimed to evaluate the influences of differences in denture teeth shade on harmony ratings and esthetic quality. Particular attention was paid to the question of how the overall variance of shade differences in the dental arch influences the perception of shade differences between adjacent teeth. (2) A total of 51 pictures of upper front teeth with standardized different colors of the left central incisor and different color variance of the dental arch were created. Eighty participants without dental knowledge and of different age, sex and educational level rated the pictures on a visual analogue scale from 0 (strongly disagree) to 100 (strongly agree) with regards to esthetic and color equality. (3) Results: The color differences between two teeth were judged in a negative linear correlation to the evaluation of color and esthetic quality. There was a sex- and education-specific difference in color and harmony ratings. In relation to the age of the participants, there was a significant difference in the color rating (p = 0.01) but not in the harmony rating (p = 0.27). Lower rating of color difference and harmony was found for a color difference in the dental arch up to ΔE = 3.1. In contrast, higher color differences resulted in higher ratings. (4) There is an influence of personal parameters on color perception. Color inhomogeneity in a dental arch leads to significant differences in color and harmony rating in a non-linear relation.

Rapid Color Quality Evaluation of Needle-Shaped Green Tea Using Computer Vision System and Machine Learning Models.

Color characteristics are a crucial indicator of green tea quality, particularly in needle-shaped green tea, and are predominantly evaluated through subjective sensory analysis. Thus, the necessity arises for an objective, precise, and efficient assessment methodology. In this study, 885 images from 157 samples, obtained through computer vision technology, were used to predict sensory evaluation results based on the color features of the images. Three machine learning methods, Random Forest (RF), Support Vector Machine (SVM) and Decision Tree-based AdaBoost (DT-AdaBoost), were carried out to construct the color quality evaluation model. Notably, the DT-Adaboost model shows significant potential for application in evaluating tea quality, with a correct discrimination rate (CDR) of 98.50% and a relative percent deviation (RPD) of 14.827 in the 266 samples used to verify the accuracy of the model. This result indicates that the integration of computer vision with machine learning models presents an effective approach for assessing the color quality of needle-shaped green tea.

Effect of Local Fermentation on Sensory, Nutritional and Microbiological Quality of “Bobolo” (<i>Manihot esculenta Crantz</i>)

Bobolo is a thick fermented, popular traditional food, derived from cassava (<i>Manihot esculenta Crantz</i>) in Cameroon. The physical, sensory, chemical and microbiological characteristics of Bobolo were analyzed, in order to identify the suitable cassava varieties and the local fermentation method with the best nutritional and industrial properties. The range of L* (lightness / darkness), a* (redness / greenness), b* (yellowness / blueness) were 75.00±0.65-80.07±0.60, 3.7±0.57-4.90±0.60, 11.9±08-17.2±0.75 respectively. Sensorial characteristics (color, pasting, and global quality) evaluation reveal that Bobolo made with aerobic fermentation with ferment had the best characteristics and independent of varieties. The campo varieties presented superior characteristics compared to the other varieties. Bobolo of different varieties and the same processed cassava products had an average range of moisture content (40.85±0.91 – 44.36±0.33%), carbohydrates (38.72±0.66 – 40.91±1.12%), protein (1.18±0.04 – 1.44±0.01%), total fat (4.02±0.05 – 4.38±0.14%), crude fiber (1.71±0.05 – 2.77±0.15%), ash (0.28±0.05 – 0.36±0.02%) and cyanure (4.28±0.22 – 6.49±0.12mg/kg) and where they varied significantly between products and variety. The mineral analysis result in the Bobolo samples ranged 0.04±0.00 - 0.07±0.00 mg/100 g Ca, 0.07±0.00 – 0.10±0.00 mg/100 g Mg, 0.74±0.05 – 0.88±0.04 mg/100 g K, 7.82±0.87 – 11.96±1.00 mg/100 g Na, 5.7±0.14 – 8.7±0.14 ug/g Zn and 15.37±0.18- 21.15±0.77 ug/g Mn respectively. The Bobolo produced contained more mesophilic total flora and molds and yeasts and was absent from <i>Eschericha coli, Staphylococcus aureus, Clostridium </i>spp.<i> Bacillus cereus </i>and<i> Salmonella </i>spp. Therefore, the types and varieties of cassava fermentations influence the quality of Bobolo.

The new preferred memory color (PMC) chart

AbstractA color rendition chart, the preferred memory color (PMC) chart, has been produced. It comprises 30 colored patches, divided into three groups: preferred memory colors, reference color‐gamut colors, and a gray scale. The main purpose of the new chart is to enable users to produce satisfactory preferred color reproduction using digital cameras, displays, and printing systems. The methods used to develop the various colors, and the color specification of each color are presented. Finally, several potential applications of the chart for the characterization of imaging devices, for the evaluation of image color quality, and for the calculation of color rendering indices for lighting are suggested.

125 Relationship of electrical conductivity to color variables (chroma, hue, L*, a*, b*) of fresh beef loins

Abstract Appraisal of beef color and overall quality assessment by consumers may be variable. In this study, Prime Grade beef strip loins were used to determine if electrical conductivity measurements (ECM) are correlated with color variables (chroma, hue, L*, a*, and b*) and could be used to improve color quality assessment and evaluation. An experimental design consisting of 6 full strip loins x 6 steaks per loin x 2 locations per steak was used and provided 72 total observations for analysis. Electrical conductivity measurements (ECM) procedures developed in our lab consisted of using emulsified meat samples concealed in silicon vessel connected to copper electrodes leading to a digital multimeter. ECM was measured in microsiemens (µS) over 60 sec with a sampling rate of 2/sec. Color variables were measured using a Varian Cary 50 Series Spectrophotometer following procedures of AMSA to ensure standardization. Data were analyzed using ANOVA and Pearson correlation coefficients. ECM means in microsiemens (µS) were 14.37, 42.52, 34.86, 22.89, 16.05, and 24.70 for the six groups of fresh steaks and were not different (P > 0.05). However, ECM values for cooked steaks differed (P < 0.05). Mean values for chroma, hue, L*, a*, and b* were different (P < 0.05) across fresh loin steaks. Correlations of ECM to all five of the color variables were different and negative (P < 0.05): chroma -0.013, hue -0.050, L* -0.009, a *-0.031, b* -0.110. These data show that ECM provide another analytical procedure that may be used in evaluating the color of fresh beef loins, and in the overall assessment and evaluation of beef products.

Color-Causing Mechanisms of Guatemala Jadeite Jade: Constraints from Spectroscopy and Chemical Compositions

The jadeite jade in Guatemala exerts remarkable commercial quality, which has attracted wide attention. Guatemalan jadeite jade displays a rich variety of colors; however, the color formation of this jadeite jade has not been systematically investigated to date. In this paper, we study different colors of jade samples to trace the compositions and color-causing mechanisms through petrography, X-ray fluorescence spectroscopy (XRF), Fourier transform infrared spectroscopy (FTIR), laser Raman spectroscopy (LRS), and UV-visible absorption spectroscopy (UV-Vis), as well as electron probe microanalysis (EPMA). The results show that jadeite and omphacite are the main mineral compositions of Guatemalan jadeite jade, together with minor albite and other impurities. The color of Guatemala jadeite jade is mainly related to Cr3+, Fe2+, and Fe3+, of which a small amount of Cr3+ causes the jadeite jade to be emerald green. Moreover, 1~2% FeO contents can lead to the blue or gray color of the samples, while the Fe3+ makes the sample dark green. The green color of some Cr3+-free jadeite is caused by the electron transition between bands of Fe3+, and the green color is related to the iron content. Moreover, the chemical composition analysis shows that some metallic elements existed in Guatemalan jadeite jade, such as Ca, Ti, Al, Si, Ni, Fe, Mn, Cr, Na, Mg, and Sr, and some trace elements were lost or unevenly distributed, which may lead to the heterogeneity of the color of the samples. Our present investigation provides insights into color discrimination, quality evaluation, and identification of Guatemala jadeite jade.

The Analysis of Underwater Imagery System for Armor Unit Monitoring Application

The placement of armor units for breakwaters in Indonesia is still done manually, which depends on divers in each placement of the armor unit. The use of divers is less effective due to limited communication between divers and excavator operators, making divers in the water take a long time. This makes the diver's job risky and expensive. This research presents a vision system to reduce the diver's role in adjusting the position of each armor unit. This vision system is built with two cameras connected to a mini-computer. This system has an image improvement process by comparing three methods. The results obtained are an average frame per second is 20.71 without applying the method, 0.45 fps for using the multi-scale retinex with color restoration method, 16.75 fps for applying the Contrast Limited Adaptive Histogram Equalization method, 16.17 fps for applying the Histogram Equalization method. The image quality evaluation uses the underwater color quality evaluation with 48 data points. The method that has experienced the most improvement in image quality is multi-scale retinex with color restoration. Forty data have improved image quality with an average of 14,131, or 83.33%. The number of images that experienced the highest image quality improvement was using the multi-scale retinex with color restoration method. Meanwhile, for image quality analysis based on Underwater Image Quality Measures, out of a total of 48 images, the method with the highest value for image quality is the contrast limited adaptive histogram equalization method. 100% of images have the highest image matrix value with an average value is 33.014.

Developing a Quality Evaluation System for Color Reproduction of Color 3D Printing Based on MATLAB Multi-Metrics.

Color 3D printing has been widely used in many fields such as cultural, medical, industrial, and food. The color reproduction accuracy of 3D printed products in these fields is becoming increasingly demanding, which requires more reproduction methods and practical tools. At present, most color 3D printing devices use one quantitative index, that is, color difference, to directly predict the color reproduction quality. However, this single quantitative index is not optimal for the curved surface of 3D printed color objects. Based on color evaluation principles, in this study, five new quantitative metrics consisting of color gamut comparison index, color SSIM index, color FSIM index, iCID index, and subjective scaling values are proposed for comparison, and the corresponding GUI design and code implementation of new color quality evaluation system are performed by MATLAB. Moreover, the comprehensive color assessment of color 3D printed products is confirmed by utilizing standard image acquisition and microscopic imaging methods that are not limited to printing materials and sampling locations. The operation of this system is validated to provide interactivity, simplicity and high efficiency. As a result, the system can provide new valuable feedback for color separation and output calibration of color 3D printing devices.

A study on antibiotic resistance gene degradation in fresh produce using peracetic acid combined with an ultraviolet-C light-emitting-diode

This study investigates the effects of peracetic acid (PAA)/ultraviolet-C light-emitting-diode (UVC-LED) treatment on the deactivation and degradation of the antibiotic-resistance gene (ARG). The deactivation rate constant for the ampicillin-resistance ( amp R ) gene encoded in plasmid pUC19 was measured using the transformation assay. The deactivation rate constant of pUC19 treated by PAA (10–50 ppm)/UVC-LED grew with an increasing concentration of PAA. At a PAA of 50 ppm, the deactivation rate constant reached its maximum: 0.16 cm 2 /mJ. Degradation rate constants for four amp R amplicons (192, 400, 603, and 851 bp) were obtained via the quantitative polymerase chain reaction (qPCR). The average degradation rate constant for the pUC19 plasmid was 1.45 × 10 −1 cm 2 /mJ with UVC-LED treatment, and 1.17 cm 2 /mJ with the PAA/UVC-LED treatment. Using PAA/UVC-LED, the deactivation rates for the amp R gene on the tomato and cabbage surfaces were 2.69 × 10 −2 cm 2 /mJ and 2.48 × 10 −2 cm 2 /mJ, respectively. Through color quality evaluation for each fresh produce confirmed that ARG could be effectively controlled using the PAA/UVC-LED treatment without affecting the color quality of fresh produce. In this study, the ARG control effect using the PAA/UVC-LED treatment was identified both in water and on fresh produce surfaces, which have a high risk of ARG exposure. • Deactivation effect of ARG in water by PAA/UVC-LED treatment according to PAA concentration was determined. • ARG degradation in water by PAA/UVC-LED treatment was measured using qPCR with different lengths of target amplicon. • Kinetics of deactivation and degradation of ARG treated by PAA/UVC-LED were analyzed and compared. • Control effect of PAA/UVC-LED treatment on ARG at the surface of fresh produce was determined.

Single underwater image enhancement based on differential attenuation compensation

High quality underwater images and videos are important for exploitation tasks in the underwater environment, but the complexity of the underwater imaging environment makes the quality of the acquired underwater images generally low. To correct the chromatic aberration and enhance the sharpness of underwater images in order to improve the quality of underwater images, we based on the differential compensation proposed a Differential Attenuation Compensation (DAC) method. The underwater image is contrast stretched to improve the contrast of the image, as well as the underwater image is denoised, for the red channel with serious loss of detail information we choose the blue and green channels with more detail information to compensate for this, and finally the image is restored through the grayscale world to obtain more realistic colors. Our method is qualitatively and quantitatively compared with multiple state-of-the-art methods in the public underwater image dataset, underwater image enhancement benchmark (UIEB) and enhancing underwater visual perception (EUVP), demonstrating that the underwater images processed by our method better resolve the problems of chromatic aberration and blur, with more realistic color, detail and better underwater image quality evaluation indicators

Colour Quality Evaluation of Bluish-Green Serpentinite Based on the CIECAM16 Model

The CIECAM16 colour appearance model is currently a model with high prediction accuracy. It can solve the problem of predicting the influence of different observation conditions on the colour of gemstones. In this study, a computer vision system (CVS) was used to measure the colour of 59 bluish-green serpentinite samples, and the tristimulus values were input into the CIECAM16 forward model to calculate the colour appearance parameters of serpentinite under different surrounds, illuminances, and light sources. It was found that the darkening of the surround causes the lightness and brightness to increase. Pearson’s r of brightness and colourfulness with illuminance is 0.885 and 0.332, respectively, which predicts the Stevens and Hunt effects. When the light source changes from D65 to A, the calculated hue angle shifts to the complementary area of the A light source, which is contrary to the CVS measurement result. The D65 light source is more suitable for the colour presentation and classification of bluish-green serpentinite.

Isolation of Pseudomonas aeruginosa for bacterial pigment production and its application on synthetic knitted fabric

This study concentrates on the isolation of bio colour producing bacteria from goat droppings and application of its colour pigment in the textile dyeing process. The isolated strain is subjected to biochemical as well as molecular characterization and is identified as Pseudomonas aeruginosa using thin layer chromatography. An optimum condition for production of pigment ‘Pyocyanin (blue-green)’ has been studied by one-factor at a time approach. The pigment (Pyocyanin) is extracted using chloroform, and 0.2N hydrochloric acid. The application of this extracted bio color as coloring agent on polyester fabric has also been studied, and it is found that the color retained on the fabric is yellow, which is different from the extracted pigment colour. Color quality evaluation of dyed polyester fabric has been performed with references to international standard protocols. The color producing is found to be 1-hydroxyphenazine, obtained by the hydrolysis of Pyocyanin at high temperature (130 o C). This 1-hydroxyphenazine imparts the yellow shade to polyester fabric on dyeing.

A learning-based approach to automatically evaluate the quality of sequential color schemes for maps

ABSTRACT Color quality evaluation is key to judging map quality, which can improve data visualization and communication. However, most existing methods for evaluating map colors are tedious and subjective manual methods. In this paper, we study sequential color schemes, a widely used map color type and propose a learning-based approach for evaluating the color quality. The approach consists of two steps. First, we extract and characterize the cartographic factors for determining the quality of sequential color schemes, such as color order, color match, color harmony, color discrimination and color uniformity. Second, we present a model to predict the color quality based on AdaBoost, a type of ensemble learning algorithm with excellent classification performance and use these factors as input data. We conduct a case study based on 781 samples and train the AdaBoost-based model to predict the quality of sequential color schemes. To evaluate the model’s performance, we calculated the area under the receiver operating characteristic (ROC) curve (AUC). The AUC values are 0.983 and 0.977 on the training data and testing data, respectively. These results indicate that the proposed approach can be used to automatically evaluate the quality of sequential color schemes for maps, which helps mapmakers select good colors.

Advanced Surface Color Quality Assessment in Paper-Based Full-Color 3D Printing.

Color 3D printing allows for 3D-printed parts to represent 3D objects more realistically, but its surface color quality evaluation lacks comprehensive objective verification considering printing materials. In this study, a unique test model was designed and printed using eco-friendly and vivid paper-based full-color 3D printing as an example. By measuring the chromaticity, roughness, glossiness, and whiteness properties of 3D-printed surfaces and by acquiring images of their main viewing surfaces, this work skillfully explores the correlation between the color representation of a paper-based 3D-printed coloring layer and its attached underneath blank layer. Quantitative analysis was performed using ΔE*ab, feature similarity index measure of color image (FSIMc), and improved color-image-difference (iCID) values. The experimental results show that a color difference on color-printed surfaces exhibits a high linear correlation trend with its FSIMc metric and iCID metric. The qualitative analysis of microscopic imaging and the quantitative analysis of the above three surface properties corroborate the prediction of the linear correlation between color difference and image-based metrics. This study can provide inspiration for the development of computational coloring materials for additive manufacturing.

Radial Basis Function Neural Network for the Evaluation of Image Color Quality Shown on Liquid Crystal Displays

The color quality of an image shown on a liquid crystal display (LCD) can be measured with a spectroradiometer; however, this instrument is expensive, work under controlled illumination conditions with an artificial source of light, and measurements take a long time. A spectroradiometer returns measurements of wavelength or CIE color space. A low-cost and fast alternative consists of using a digital camera that outputs RGB measurements. Unfortunately, comparisons between measurements obtained with both instruments cannot be performed; hence, conversion equations must be used. The main problem is that equations do not consider the effects caused by the camera lens, sensor variations, and configurable parameters such as gain and the exposure time. This paper proposes the architecture of a radial basis function neural network (RBFNN) to measure the image color quality displayed by an LCD using a digital camera. The RGB values acquired with a camera are used as inputs to the RBFNN. The output predicted the luminance and chromaticity components in the CIExyY color space and included the corrections to the lens and camera parameters. First, the RBFNN topology is explained, including the calculation of the number of neurons in the hidden layer, and the definition of the dispersion centers and their associated spread. Next, the experiments related to RGB color space reconstruction and conversion from RGB to CIE are presented. The proposed approach was tested on a real automotive scenario. The results obtained were similar to those measured with the spectroradiometer with an accuracy of 93.3%. Moreover, the results remained within limits established by the six-sigma methodology.

Color quality and antioxidant activity evaluation of clown loach juvenile, Chromobotia macracanthus Bleeker 1852 by addition of astaxanthin in diet

Botia or clown loach is the one of fishes was originated from Indonesia and as an ornamental fish commodity in the global market. Clown loach both nature and cultured have some problems when reared in aquaria that is the decrease of color quality. An innovation technology to improve color quality through diet formulates is needed. The aims of this research were to increase the color quality using astaxanthin in diet and to find out the role of astaxanthin as antioxidant in clown loach. The study consists of four treatments of astaxanthin dosages in the diet with isoprotein and isoenergy, namely 0, 50, 100 and 150 mg kg-1 with four replications. The fish juveniles with size of 3.44±0.51 cm and 0.56±0.02 g of weight with density of one fish per littre were used. The test diet was given three times a day during 60 days. The results showed that there were no significant differences antioxidant activity such as superoxide dismutase enzymes and malondialdehyde. However, there was a significant effect (P<0.05) to color quality of the chroma and total carotenoid, whereas no significantly different in lightness. The addition of astaxanthin was effective to improve the color quality of clown loach juvenile. Thus, 100 mg kg-1 of astaxanthin in diet is an optimal dose for clown loach juvenile.

A high‐precision method evaluating color quality of Sichuan Dark Tea based on colorimeter combined with multi‐layer perceptron

AbstractInstrumental examination of Sichuan Dark Tea (SDT) quality instead of human panel sensory evaluation is important for quality control. This study attempted to create a high‐precision method to rapidly and accurately evaluate SDT color quality. Colorimeter combined with multi‐layer perceptron (MLP) was utilized to extract CIELAB color parameters of dried tea, liquor, and infused tea, respectively, and established the prediction models of color attributes scores with the optimal color parameters selected by a principal component analysis (PCA). MLP models established could accurately predict color total scores of SDT, the glossiness of dried tea, and chroma of infused tea (Rp = 0.889–0.989; RMSEP = 0.393–0.631). Besides, models based on tea pigments could accurately predict infused tea color total scores (Rp = 0.920, RMSEP = 0.531). Parameter a* was significantly correlated with almost all of the color evaluation factors of SDT and seemed to be the characteristic color parameter. The color quality of Sichuan Dark Tea can be excellently estimated by the method utilizing colorimeter coupled with MLP.Practical applicationsTo meet the requirement of dark tea production and the costumer's expectation, this study attempted to create a high‐precision method quickly and accurately evaluating color quality of SDT. Usually, in the massive production, tea color evaluated by eyesight is time‐consuming, subjective, and has poor accuracy due to visual fatigue of human. In this work, we optimized color parameters with PCA to improve the performance of MLP models established. The results can provide a theoretical basis for the evaluation of tea color quality by instrument, and make SDT quality control more convenient, accurate, and time‐saving.

Color quality evaluation of Chinese bronzeware in typical museum lighting.

A series of psychophysical experiments have been conducted to investigate the effect of light sources on the color appearance of Chinese bronzeware. Three groups of 30 observers were asked to evaluate a set of Chinese bronzeware under different light sources in three paired-comparison experiments-one group of observers for each experiment. The visual attributes of color preference, color comfort, color discrimination, and antiquity were scaled. A panel of seven light sources of 3000 K, with Duv values ranging from $ - {0}.{015}$-0.015 to 0.015, was used in Experiment 1. A second panel of seven light sources of 4000 K, with a similar range of Duv values, was used in Experiment 2. For Experiment 3, six light sources were chosen from Exps. 1 and 2, plus four lights of 2700 K, 3300 K, 3700 K, and 4300 K, with Duv values of zero. These experimental lights produced a constant illuminance of approximately 200 lux in a pair of viewing booths, and their color rendering indices were between 88 and 95. The results showed that the subjective judgments for color preference and color comfort were highly correlated while the whiteness of the lighting strongly influenced the perception of color preference, comfort, and discrimination. A light source of 4000 K with a Duv value of zero exhibited the best color preference and color comfort performance, while observers were found to show the greatest capability for color discrimination under a light source of 4000 K with a Duv value of $ - {0}.{015}$-0.015. In addition, the bronzeware appeared to have greatest antiquity when illuminated by a 3000 K light source with a Duv value equal to 0.005. Based on the psychophysical data, the performance of typical color quality metrics were also tested in relation to the four scaled visual attributes.

Color calibration for fabric image analysis based on spectral reflectance reconstruction

Spectral characterization can be used for the color calibration of the fabric image to eliminate the influence of the imaging equipment and illumination environment, so as to obtain the actual yarn color information of the fabric image and improve the accuracy of fabric color analysis and rendering. However, existing algorithms based on spectral reflectance reconstruction were not ideal to minimize the obvious c between the reconstructed and its actual color. Compared with the index of spectral reflectance reconstruction accuracy, the chromaticity error is a direct index of image color quality evaluation by human vision. Therefore, to eliminate the influence of imaging equipment and illumination environment on the fabric image color occurring during the fabric image acquisition, a novel color calibration method based on spectral reflectance reconstruction was proposed for fabric image analysis in this paper, which focused on the optimal selection of representative colors and defined a new spectral reconstruction error evaluation function E=αErmse+βECA. Experimental results show that the proposed method in this paper is superior to the existing methods in color reconstruction accuracy and visual quality.

Use of Ferro Frit 3110 in Developing Glazes for Omani Earthenware Clays: Evaluation of Color Quality for Ceramic Decoration in High Schools

In this studio and laboratory research study, the suitability of several glazes for use on the earthenware clays used by local potters in the internal provinces of Oman was investigated. The aim was to develop suitable, economic glazes from local materials for use with Omani earthenware clays that could form an adequate adhesive bond with the clay surface and be used in ceramics decoration in local educational institutions. In particular, the experiments in this study mainly evaluated the use of Ferro Frit 3110 in different glazing recipes. It is a calcium- and sodium-rich frit with oxides that are stable and predictable, and it is more dependable in chemical composition than other raw materials. The final results can help to reduce the cost of importing ready-made expensive glazes from overseas for use in ceramics decoration in Omani higher educational institutions.