Color Analysis Research Articles

Mango Tree Dataset for Yield Estimation: Some Exploratory Analysis

Objectives: Employing computer vision methods for yield estimation requires standard datasets. However, unavailability of such a dataset in the literature limits the researchers from evaluating and comparing the performance of their proposed algorithms. In this paper, a benchmark of mango tree dataset is introduced. Methods: The dataset is gathered over a 5-month period, starting from the fruit's blossoming stage and ending with its ripening stage. There are 21,000 photos of 4 distinct mango tree varieties in the dataset. From each cultivar, images are captured with different views, distances, and daylight conditions. Further, preprocessing, and exploratory analysis of the dataset are carried out by extracting a few global features such as colors, textures, and histograms for intra-class and inter-class mango trees. Findings: The analysis of the collected dataset with different color layers by extracting a few global features and classification of the cultivars of mango trees and, based on the results obtained, the optimal layer of color is attained for the further yield estimation process. Novelty: Exploratory analysis of a novel temporal mango crop dataset is executed, and a color analysis classification method is proposed to aid in the early estimation of mango fruit crop yields. Keywords: Mango Fruit, Yield Estimation, Temporal Dataset, Feature Extraction, Tree Classification

Skin Color Analysis of Various Body Parts (Forearm, Upper Arm, Elbow, Knee, and Shin) and Changes with Age in 53 Korean Women, Considering Intrinsic and Extrinsic Factors.

Background/Objectives: Skin color is innately determined by race and other genetic factors, and it also undergoes acquired changes due to various intrinsic and extrinsic factors. Previous studies on skin color have mainly focused on the face, and research has recently expanded to other body parts. However, there is limited information about the age-dependent changes in the skin color of these body parts. The purpose of this study is to analyze the differences in skin color between various body parts and the changes in skin color of each body part with age. Methods: This study examined the skin color of 53 Korean women subjects evenly distributed in age from the 20s to 60s on several body parts: forearm, upper arm, elbow (extended or folded), knee (extended or folded), thigh, and shin. The lightness (L*), redness (a*), and yellowness (b*) were measured using a spectrophotometer, and the individual typology angle (ITA°) was calculated from the L* and b* values. The melanin index and erythema index were measured using the mexameter. Results: The results showed that the elbow skin had the lowest L* and ITA° values and the highest a* and b* values among the examined body parts, followed by the knee. The melanin index and erythema index were also high in the skin of these body parts. In the analysis of age-dependent changes in the skin color of various body parts, the forearm skin exhibited the most notable decrease in the L* and ITA° values and increases in the a* and b* values, followed by upper-arm skin. The melanin and erythema indices in the forearm also increased as the subjects aged, whereas those in the elbow and knee rather decreased with age. Conclusions: This study suggests that differences in intrinsic and extrinsic skin aging in various body parts may be expressed as different changes in skin color and raises the need for cosmetic and dermatological research to identify the physiological significance of these changes.

Detection of honey adulteration by characterization of the physico-chemical properties of honey adulterated with the addition of glucose–fructose and maltose corn syrups

This study aimed to experimentally investigate the effect of sugar syrup additions on quality measurements of honey and to detect adulteration. For that purpose, two different pure blossom honey samples were adulterated by directly mixing 0%, 5%, 10%, 20%, 30%, 40%, and 50% of commercially available glucose–fructose corn syrup and maltose corn syrup. In this regard, key physico-chemical properties like moisture, pH, free acidity, proline, diastase number, color (L, a, b and Delta-E), electrical conductivity, HMF, sugar profile (glucose, fructose, sucrose and maltose), and C4 sugar analysis were tested. The results of the individual analysis of moisture, pH, free acidity, proline, diastase number, color, electrical conductivity, and HMF failed to detect sugar syrup adulteration. However, when principal component analysis (PCA) was utilized to analyze the data gathered from these tests, adulterations at all-syrup ratios (5–50%) were successfully detected.Graphical

Development and characterization of high nutritional value snack bar as a complementary source of nutrients in supporting the growth of pregnant women: chemical, physical, and sensory properties

Developing high nutritional value pregnant bar products as a source of different nutrients to support daily-consumed poor is considered a practical goal to increase pregnant crucial nutrient intake. This research aims to develop high nutritional snack bar as a complementary to support the nutrient requirements in pregnant women using a mixture of grains (chickpea and quinoa flours) along with wheat flour in addition to chia seeds, inulin, moringa leaves powder, anise, mastic and stevia. This study was conducted in two stages. Seven treatments of quinoa and chickpea flour levels in the ratio of (1:2) with wheat flour were produced. Proximate analysis, physical proprieties, color analysis, and sensory evaluation tests were determined. This highly nutritional snack bar has larger contents of protein, fiber, lipids, and ash, as well as lower amounts of moisture and carbohydrate content compared to wheat flour control. Moreover, physical properties: snack bar samples’ weight, diameter and thickness decreased as the concentration of chickpea and quinoa flours increased. The results of the color analysis showed that there were significant differences in lightness (L*), redness (a*), and yellowness (b*) values between the control and the seven snack bar treatments, which showed lower lightness (L*) and yellowness (b*) color values and higher redness (a*) color values. Regarding the sensory evaluation, the most accepted treatment was treatment 7, which had 47.5% wheat flour, 35% chickpea flour, and 17.5% quinoa flour. Developing a high-nutrient-value snack bar as a complementary source of nutrients to support and cover most pregnant women’s nutrient requirements, maintaining necessary daily needs with controlled calorie intake and high quality and acceptability.

Literature Review: Skin Cancer Types Detection Using Deep Learning

Skin cancer ranks among the swiftly proliferating diseases globally, exacerbated by the limited resources. Timely recognition of skin cancer holds paramount importance for precise diagnosis and identification, facilitating a preventative approach overall. The incidence of melanoma, the most perilous type of cancer of the skin, is increasing. Identifying skin cancer in its initial phases poses a challenge for dermatologists. Over the past few years, both supervised and unsupervised learning assignments have extensively employed deep learning techniques. Among these, Convolutional Neural Networks (CNN) has outperformed its counterparts in tests related to object detection and classification. The algorithm used here relies on a bank of directional filters (difference of Gaussians) and explores color, directionality and topological properties of the network. Dull Razor algorithm has been used to remove artifacts such as hair as they cause difficulties in detecting pigments. Keywords— Deep learning, Convolutional Neural Networks (CNN), Color analysis, Data Augmentation, Artifacts removal, Pigment detection.

Middle to late Holocene climate change in the monsoon-dominated southeastern Tibetan Plateau and its relationship with human activity

Aeolian deposits on the southeastern Tibetan Plateau (SETP) can provide evidence of how prehistoric humans were influenced by climatic and environmental changes in high-altitude regions. We present the results of multi-proxy analyses of a middle–late Holocene aeolian section in the SETP, together with the probability density of the ages of various cultural sites within and around the study area. Quartz optically stimulated luminescence dating provides a reliable chronology for this section, and analyses of geochemical elements, color and grain size are used to reconstruct the pattern of climate change during the middle–late Holocene. The results suggest a trend of gradually decreasing moisture from the middle Holocene (∼6 ka) onwards, followed by a slight increase at ∼2 ka, which is supported by TraCE-21 ka simulation results. These changes were closely related to variation in the Indian summer monsoon (ISM) caused by decreasing Northern Hemisphere summer insolation and an increase in the Atlantic Meridional Overturning Circulation. The variations in dust activity are inversely related with moisture and there was a significant decrease in dust activity after ∼2 ka. The drought conditions during the 4.2 ka event recorded within the section appear to be a continuation of the trend of middle–late Holocene climatic deterioration, which is superimposed on a weakening trend of the ISM. The permanent human occupation of the study area after ∼2 ka corresponded to an interval of mild and wet climate when dust activity was relatively weak. An observed correlation between the intensity of human activity and dust storms suggests that the enhancement of human activities played a significant role in increasing the occurrence of dust storms. Overall, our results provide new insights into human-environmental interactions in the SETP.

Color and texture analysis of glucomannan modified growol cookies for diabetic

Color and texture analysis of glucomannan modified growol cookies for diabetic

A framework connecting vision and depiction

ABSTRACT We present a framework that connects ideas from the visual arts and visual perception. It adapts two existing frameworks for the analysis of form and content so that it can be used in an educational context for teaching perception through visual arts. The basis is the formal analysis of texture, colour, light, space, and material. This analysis can be conducted both on the medium and the motif, which adds a second level in addition to the formal level. Thirdly, a conte(n/x)t level is discussed which combines a basic notion of semiotics and iconography. We share our experience of implementing pictorial analysis in design and perception education and discuss how the framework is used both in a quantitative and a qualitative fashion. Next to education, the framework provides a basis for further pictorial research.

Rapid analysis and classification of blue ballpoint pen inks using high-performance thin-layer chromatography and digital color analysis

Despite the rise of digitalization, the scrutiny of paper documents with stamps and signatures remains crucial, constituting 55–60 % of document examination court cases. Developing accessible and robust ink analysis techniques is an ongoing challenge for forensic scientists. To tackle issues related to the identification and classification of dye components in blue ballpoint pens, we have proposed an advanced approach that integrates high-performance thin-layer chromatography (HPTLC), digital color analysis (DCA), and hierarchical cluster analysis (HCA) for a simplified yet effective procedure.The method encompasses multiple development of TLC plates. Initial separation employs methanol:ethanol (4:1, v/v), followed by a second separation using methanol:propan-2-ol:formic acid (1:1:0.1, v/v/v) to achieve cationic dye separation. This TLC development enhances separation selectivity, contributing to a more precise clustering of pen inks. Employing advanced DCA as a processing method for HPTLC, the optimal descriptor for ink classification is identified as the difference between red (R) and green (G) color components. The proposed clustering algorithm achieved 8 distinct ink clusters, showing improved discriminative capability and a reduced variable space compared to well-established or state-of-the-art methods.The approach's robustness was demonstrated across different readout devices, including smartphones and scanners. Reproducibility tests yielded consistent clustering results, confirming the method's reliability. Moreover, the method proved effective in clustering pen ink extracts from paper substrates, showcasing its potential for real sample analysis.This HPTLC-DCA approach presents a simple, cost-effective, and high-precision solution for clustering blue pen inks, significantly enhancing accessibility in high-throughput forensic applications.

Quantitative analysis methods for evaluating colour on architectural heritage: survey of colour restoration and perception of the Wen Yuan Ge in the Forbidden City

Three methods can be used to evaluate the colour used on architectural heritage: manual evaluation, instrumental measurement, and process restoration. Optical instruments that can obtain relatively accurate chromaticity data are ideal. As architectural heritage sites age, their colour fluctuates. Researchers must screen colour data and analyse the features based on experience with colour perception. This study combines quantitative colour analysis and a scaled perception survey to analyse the Wen Yuan Ge in the Forbidden City and provide a new reference for researching and designing colour in architectural heritage.

Bactericidal Effects and Quality Impact of Peroxyacetic Acid and Sodium Hypochlorite on Chicken Carcasses.

There is an urgent need to develop efficient and environmentally friendly decontaminants for poultry products. In this study, we aimed to evaluate the practical application of peroxyacetic acid (PAA) as a replacement for sodium hypochlorite (SH) to sterilize fresh chicken carcasses, using microbial, color, and electronic-nose analyses. We evaluated the decontamination effects of different concentrations of PAA and SH on chicken carcasses. The bactericidal effects of PAA at pH 3, 7, and 9, and SH at pH 10, at concentrations ranging from 100 to 500 ppm on coliform bacteria, total bacteria, and Salmonella spp. were evaluated. PAA induced a similar bactericidal effect at lower concentrations than SH. Therefore, at the same concentration and treatment time, PAA showed better bactericidal effects than SH. Although treatment with PAA (pH 3) and SH (pH 10) resulted in considerable discoloration, the degree of discoloration decreased when the pH of PAA was increased to 7 and 9. Therefore, by increasing the pH of PAA, the discoloration effect on chicken carcasses can be reduced without altering the microbial-reduction effect. Electronic-nose analysis showed that the flavor of the chicken was almost unaffected by volatile components at a treatment time < 30 min. Therefore, this study experimentally identified the optimal PAA concentration for the decontamination of chicken carcasses. The study findings provide a theoretical basis for the replacement of traditional bactericides, such as SH, with PAA for the production of poultry products.

Soil Color Comparison Using Munsell Soil Color Chart and Calibrated Smartphone Camera

Soil color is a crucial property in soil fertility assessment and monitoring. However, the subjective nature of the Munsell Soil Color Chart (MSCC) can lead to uncertainty in the analysis. To address this issue, a study was conducted to develop a soil color classification model from smartphone digital imagery based on color analysis and MSCC. The study involved taking 26 soil samples from various soil types and locations in the Special Region of Yogyakarta, Indonesia. Digital images of the soil were taken through a smartphone camera and compared with observations using MSCC to compare color differences (ΔE) based on Lab values. Soil images obtained from indoor studio conditions and calibration using spydercheckr in indoor and outdoor conditions are compared with MSCC and Chromameter values. The L*a*b color space was found to be superior to RGB for predicting and detecting small differences in color. The study also found that the Munsell soil color chart (MSCC) had a lower color difference than the chromameter in all lighting conditions, indicating that the MSCC or visual assessment can better detect the main soil color or soil matrix, while chromameter readings may have errors due to soil impurities.

Diverse material properties and morphology of moth proboscises relates to the feeding habits of some macromoth and other lepidopteran lineages.

Insects have evolved unique structures that host a diversity of material and mechanical properties, and the mouthparts (proboscis) of butterflies and moths (Lepidoptera) are no exception. Here, we examined proboscis morphology and material properties from several previously unstudied moth lineages to determine if they relate to flower visiting and non-flower visiting feeding habits. Scanning electron microscopy and three-dimensional imaging were used to study proboscis morphology and assess surface roughness patterns on the galeal surface, respectively. Confocal laser scanning microscopy was used to study patterns of cuticular autofluorescence, which was quantified with colour analysis software. We found that moth proboscises display similar autofluorescent signals and morphological patterns in relation to feeding habits to those previously described for flower and non-flower visiting butterflies. The distal region of proboscises of non-flower visitors is brush-like for augmented capillarity and exhibited blue autofluorescence, indicating the possible presence of resilin and increased flexibility. Flower visitors have smoother proboscises and show red autofluorescence, an indicator of high sclerotization, which is adaptive for floral tube entry. We propose the lepidopteran proboscis as a model structure for understanding how insects have evolved a suite of morphological and material adaptations to overcome the challenges of acquiring fluids from diverse sources.

Optimising Technological Treatments with the Taguchi Approach to Reduce Acrylamide and Improve Colour Properties in Potato Chips

Today, consumer demand for food safety, especially in fried foods, is increasing. In the first place, it is demanded to reduce the amount of food toxins, in particular toxins resulting from the thermal process such as acrylamide. This study aimed to examine the effect of different technological treatments on the optimisation of minimum acrylamide and maximum colour properties by applying the Taguchi approach in the production of chips. In this study, design of experiments, signal-to-noise (S/N) ratio, analysis of variance, and regression analysis methods were used to optimise the minimum acrylamide and redness (a*), maximum brightness (L*), and yellowness (b*) values. The optimal parameters for acrylamide were found to be 90 °C slice washing temperature, 175 °C frying temperature, and 175 s frying time. The optimal parameters for colour analysis were determined as 30 °C slice washing temperature, 175 °C frying temperature, and 175 s frying time. Analysis of variance showed that frying temperature and time had a significant (p < 0.05) effect on the results. It was determined that a decrease in frying temperature and time led to a decrease in the amount of acrylamide and redness and an increase in brightness and yellowness. According to the results of the analysis of variance, the most effective technological treatments were frying temperature with effect rates of 37.45% and 60.26% for acrylamide and L* values, respectively, and frying time with effect rates of 40.50% and 44.19% for a* and b* values, respectively. As a result of the study, through the Taguchi method, while quality features in chips were preserved, the amount of acrylamide was reduced.

Improving craft beer style classification through physicochemical determination and the application of deep learning techniques

The consumption of craft beer at fairs and festivals is a phenomenon that keeps growing in the world. For this reason, it is important to control the quality characteristics of the different styles. This study aimed to analyze the different styles of beer, classify them according to their physicochemical parameters, and propose a predictive pattern-based model known as deep learning that best defines the styles that are presented at festivals. Physicochemical analyses of final gravity, color, alcohol, bitterness, and α-acids were carried out on eight styles of beer. The first four parameters are those that characterize the styles according to the Beer Judge Certification Program style guide. The incorporation of the α-acid determination allowed a more realistic classification that considers the brewers' new tendencies. This study will lay the foundations to improve local recipes, implement standardization, and provide training to local brewers.

Expression of Concern: Oil painting color image enhancement recognition method based on artificial intelligence: applications of an AI model in environmental research

ABSTRACT Due to the pollution of the air and water environment and the problem of forgery, it is difficult to identify oil paintings. The reason is that air pollution and water pollution can lead to moisture, mold, and even water stains on the picture, which will seriously damage the integrity and color performance of the picture. At the same time, chemicals in the water may also have a corrosive effect on the oil painting, further destroying the color and detail of the picture. The problem of relying entirely on the conventional experience of experts is too subjective. Some controversial works are difficult to convince people with rational identification evidence, so it is necessary to explore a scientific and effective method to quantify the authenticity of oil paintings. This paper constructs an oil painting authenticity identification method based on multi-feature fusion based on the artistic style analysis and feature extraction of oil painting shape, color and texture. The recognition accuracy of the proposed method is compared with that of the existing neural network. The results show that the recognition rate of the proposed model is 73.0%, which is the best performance.

A NEW NATURAL FOOD DYE: MICROENCAPSULATED CORNELIAN CHERRY BIOACTIVE COMPOUNDS

Cornus mas (CM) is one of the four edible fruits of the Cornus genus, a rich source of biologically active compounds (BACs) such as vitamins (like vitamin C), carotenoids, iridoids, and phenolics (phenolic acids, anthocyanins, and other flavonoids). This study aimed to analyse the improvement of the stability of CM anthocyanins by microencapsulation, in order to propose a new natural food dye. Microencapsulation using a mixture of whey protein isolate (WPI) and chitosan (CH) as wall materials has been applied to protect anthocyanins against external factors (e.g., light, temperature, storage, etc.). Two experimental variants of microencapsulated powders, WPI:CH = 1:1 (CH1) and WPI:CH = 1:2 (CH2), were realised by varying the wall materials ratio. The cornelian cherry fruit concentrated extract was evaluated for its phytochemical, colourimetric, and antioxidant capacities. Due to the excellent anthocyanin encapsulation effectiveness (74.29 – 88.71%), the wall materials utilised for both powders can be considered effective choices to safeguard the anthocyanins. All tests performed on the microencapsulated powders demonstrated that both suggested experimental forms can serve as a healthy substitute for artificial food additives. The incorporation of cornelian cherry fruit extract and microencapsulated powders into a food matrix (jelly candies) allowed examination of their effectiveness. The colour analysis rigorously characterised all the colour parameters related to red nuances (due to anthocyanins content, such as cyanidin-3-glucoside) and yellow nuances (associated with carotenoids content).

Precision photodetector for information and measurement systems and diagnostic tools for medical purposes

The development of a new generation of diagnostic tools and medical information systems requires the use of the latest advances in the field of primary converters of physical quantities. These include photodetector devices (PDDs) made on the basis of photodiodes. The direction of this research is the identification and analysis of FPU structures that have increased accuracy in recording light fluxes. Identification of the structure of the PDA, in which errors are eliminated due to temperature and time drifts of input currents and bias voltages of the operational amplifiers included in the PDA. The structure of the original FPU, which provides increased accuracy of registration of light fluxes, is presented and analyzed. It is advisable to use the presented FPU in the development of medical diagnostic devices and information-measuring systems. A special place in their use is occupied by various kinds of optical analyzers for medical purposes, for example, a tooth color analyzer, systems for studying microcirculation of the blood flow, magnetotherapy units that use optical methods for recording the patient’s breathing process, etc. FPU will be of interest to scientists and engineers involved in the development of medical diagnostic equipment and information measurement systems.

Enhancing nutritional status, growth, and fruit quality of dried figs using organic fertilizers in rain-fed orchards: A case study in Estahban, Iran.

The majority of Iranian fig production is exported, making it one of the world's most well-known healthy crops. Therefore, the main objective of the current experiment was to investigate the effects of various types of organic fertilizers, such as animal manure (cow and sheep), bird manure (partridge, turkey, quail, and chicken), and vermicompost, on the nutritional status of trees, vegetative and reproductive tree characteristics, fruit yield, and fruit quality traits in dried fig cultivar ("Sabz"). According to the findings, applying organic fertilizers, particularly turkey and quail, significantly improves vegetative and reproductive characteristics. However, other manures such as sheep, chicken, and vermicompost had a similar effect on the growth parameters of fig trees. Additionally, the findings indicated that except for potassium, use of all organic fertilizers had an impact on macro and microelements such as phosphorus, nitrogen, and sodium amount in fig tree leaves. Also, based on fruit color analysis in dried figs, the use of all organic fertilizers improved fruit color. Moreover, the analyses fruit biochemical showed that the use of some organic fertilizers improved that TSS and polyphenol compounds such as coumarin, vanillin, hesperidin gallic acid and trans frolic acid. In general, the results indicated that the addition of organic fertilizers, especially turkey manure, led to increased vegetative productivity and improvement in the fruit quality of the rain-fed fig orchard.

Proximate, total phenolic, carotenoid, antioxidant activity, color, and FTIR analysis of red ginger powders (Zingiber officinale var. Rubrum) through the evaporation-crystallization process

Red ginger is a plant that is rich in antioxidants and is easily available in Indonesia. So far, red ginger has been used with various extraction methods by previous researchers, but the application of this process has not been able to be used by independent economic MSMEs. This research took place using evaporation-crystallization equipment as the main tool, accompanied by temperature variations (80 and 90°C) and granulated sugar as a crystallization agent (60 and 100%). The quality of the powdered red ginger product analyzed in this study showed good stability values for the fresh red ginger raw material before processing. The average value of the proximate content of red ginger products is 7.668; 12.116; 5.225; 0.422-1.708; 73.960% for moisture, ash, fat, protein, and carbohydrate content, respectively; and total glucose of 63.768 ppm. Meanwhile, the results of the phenolic and carotenoid content provide a significant reduction of up to 50%. The average content is 42.459 mg gallic acid/g; and 5.480 g respectively (including color - also a decrease in L, a, and b values) compared to the red ginger pulp raw material. The opposite value occurred in the DPPH antioxidant activity of red ginger pulp, the content of which was 2-3 times higher than fresh red ginger. These findings not only have an impact on the development of more health-beneficial food and beverage products but also encourage further understanding of the potential of bioactive compounds in ginger to support human well-being.