Color Analysis Method Research Articles

Bibliometric Analysis of the 100 Most-Cited Articles on the Methods of Shade-Matching in Dentistry.

The purpose of this bibliometric analysis is to identify the 100 most cited articles and delve into citation metrics to gain insights into the evolving trends in shade-matching methods in dentistry. Following PRISMA guidelines, two reviewers conducted a structured search in Scopus using keyword-based search strings. The top 100 articles were selected based on predefined criteria, and their bibliometric data were extracted. Harzing's Publish Or Perish and VOSviewer were used to generate the bibliographic network. Between 1989 and 2017, the top 100 articles were published and obtained citations ranging from 560 to 48. Twenty-eight articles received over 100 citations, deemed classic. The Journal of Prosthetic Dentistry and the United States of America were the primary contributors. In-vitro experimental studies employing restorative material samples were prevalent, with spectrophotometers being the favored method of color analysis. Using Python, Spearman's correlation coefficient resealed positive correlations between citation count and age of publication (r = 0.16, p = 0.12) and between citation count and the impact factor of the journal (r = 0.35, p < 0.05). However, a negative correlation was observed between citation density and age of publication (r = -0.46, p < 0.05). This study demonstrated a significant upward trajectory of citation count in shade-matching in dentistry, reflecting high-quality scientific contributions.

Archaeometric Studies on Bricks from the Stratonikeia Ancient City in Caria

The ancient city of Stratonikeia is located within the territory of Eskihisar Neighbourhood in Yatağan District of Muğla Province. Excavations have been undertaken at the site since 1977. Settlement at the site of the ancient city is understood to go back to the second millennium BCE. At the site it is possible to see structures from a wide time span ranging from Classical Period through the twentieth century. Within the scope of the present study, a total of 25 samples were taken from seven structures within the ancient city of Stratonikeia. This study aims to cast light onto the archaeometric characters of the brick samples, to retrieve information on their production technologies, obtain data regarding their firing temperatures and their production sites as local or imports. The samples were investigated using stereomicroscope, optical microscope, color analysis, XRF, XRD, statistical and SEM-EDS methods. Various analyses led to compatible results and the brick samples were categorized into three main groups and one subgroup. It was noted that most of the samples were fired at 750-850oC and all of them were produced with clay taken from similar clay deposits.

IOT BASED COLOR AND SIZE WISE SORTING MACHINE USING CAMERA

The process of arranging items systematically is named sorting. Manual sorting of Object is preferred at the wholesale market and industries supported different parameters like size, shape, quality, etc. But it's a time consuming, less efficient, and inconsistent method. The existing systems in the market can sort single Object with single or multiple parameters. To replace this traditional sorting way, the proposed system presents an automatic Object sorting mechanism with an image processing technique. It recognizes and classifies two different Object with two different Color analysis method. Key Words: Image Processing, Python, Arduino Uno, Color Detection, IR Sensor Web Camera, Conveyor Belt.

PENERAPAN METODE NAÏVE BAYES DALAM KLASIFIKASI KESEGARAN IKAN BERDASARKAN WARNA PADA CITRA AREA MATA

As a maritime nation, fish is a staple in the Indonesian diet, rich in nutrition and a crucial protein source. It is imperative to maintain the freshness of fish to ensure the quality of fish production. However, the practice of mixing fresh and non-fresh fish poses a serious threat to consumer health and diminishes the overall quality of fish production. Therefore, the development of an automated and efficient method is necessary to distinguish between fresh and non-fresh fish. This research proposes the application of the Naïve Bayes method in classifying fish freshness based on color analysis in the eye area image. This approach involves the extraction of entropy features after segmenting fish images using the RGB and YCbCr color models. A total of 40 datasets of fish eye images were used for training and testing the model. The research results indicate that the proposed classification method achieved an accuracy rate of 97.5%. This success signifies the potential of the color analysis method and entropy features in distinguishing levels of fish freshness. These findings contribute to the development of automated techniques for monitoring and processing fish quality in the fisheries industry.

Green Sustainable Textile Supercritical Dyeing Process Using CO2 Madder (Rubia tinctorum L.) Extract

ABSTRACT Waterless or reduced water consumption dyeing methods based on supercritical technologies are of interest to fabric manufacturers. The study was aimed at developing a dyeing method for natural fibers, in particular linen and silk, by pressure supercritical impregnation using madder alizarin (R. tinctorum) coloring compound produced by supercritical extraction method as an ecological alternative to conventional dyeing methods. A comparative test of fabric dyeing using supercritical and conventional methods was also carried out. In these dyeing technologies, the pre-treatment process plays an important role in the color intensity. The tests were performed using fabrics without and with mordants, and the results were compared using the color analysis method. The colors of the dyed samples obtained in the supercritical technology are more in shades of carmine, and in the traditional method in duller reds. The proposed modern and ecological dyeing technology guarantees a good resistance to washing and light. Antibacterial activity tests were also performed using supercritical and ethanol extracts. Dyed fabrics play health-promoting and protective roles for their users. Linen fabrics showed antimicrobial activity and positive effects on the skin, which was more moisturized. Waterless technologies should be developed in conjunction with user and environmental impact studies.

Experimental Research on the Formation of the Third Body on the Friction Surface of Coal Cake Tamper Hammer Lifting Mechanism

A tamping machine is the key equipment of large coking coal cake forming in the steelmaking industry, where the loose coal is compacted into a coal cake by the reciprocating movement of its tamping hammer. In the long-term friction process, the third particle attached to the surface of the friction pair of the hammer lifting mechanism often causes the tamping hammer to slip and wear the tamping hammer friction plate, resulting in an insufficient height of the hammer, uneven work of the tamping hammer, coal cake collapse and other problems. In order to avoid the adverse effect of the third body on the surface of the friction pair, this paper studies the formation of the third body on the friction surface of the lifting hammer mechanism of the coal cake tamper. The cam material (Q345B) of the hammer lifting mechanism and the copper-based powder-metallurgy composite material of the friction plate of the tamping hammer are prepared into the pin-disk friction test disk and pin, respectively. Based on the characteristics of the friction temperature variation in the pin-disk test, an equivalent accumulation method is proposed, that is, the wear state of several samples at different wear times is equivalent to characterize the wear condition of a sample at different stages during continuous wear, and the different stages of the third body formation process are obtained. By analyzing the change of the composition of the third body and the content proportion of each element on the surface of the bottom plate at different wear times, it is determined that Cu is the key index of the third body. The content of the Cu element is used to characterize the content of the third body on the surface of the disk sample, and the formation rule of the third body on the surface of the disk is inferred. Through an image processing method of color analysis, the distribution law of the third body on the whole disk is identified. The properties of the third-body material on the disk surface are obtained by analyzing the changes of hardness and morphology at each friction stage. The results show that with the increase of friction time, the content of Cu on the disk surface increases to 22% and then decreases to 15%. The microhardness of the friction surface reaches its highest at 7 min, which is 1.4 times that of the Q345B material. The maximum disk surface roughness is 0.452 µm. Finally, the formation process of the third body is summarized in three stages: formation, equilibrium and damage. Therefore, the frictional properties of the surface of the friction pair vary from weak to strong to weak with the formation characteristics of the third body.

Analyzing the color of forensic textile using smartphone-based machine vision

Color is an important characteristic of textile, and its analysis is of great significance for the forensic characterization of textile. The colorimetry method based on visual observation provides a subjective assessment; the instrument-based color analysis method is objective but requires expensive equipment and professional technicians. In this study, a smartphone-based machine vision method for color analysis was established. A smartphone with a camera was used for image acquisition, and the free software ImageJ was used for image processing. The captured RGB image was first converted to a Lab Stack, and then the target area was selected for L*a*b* value analysis. The influence of acquisition equipment, light source, illumination/photography angle and distance, and sample on color analysis was investigated. Fifteen red textile pieces were analyzed using optimized machine vision methods, and the results were compared with those obtained using the microspectrophotometry by both hierarchical cluster analysis and K-means clustering method. The results of the two methods were consistent, thereby confirming the reliability of the machine vision method. The smartphone-based machine vision color analysis method is cheap, simple, accurate, and objective; thus, it has great potential to be widely used in forensic science.

부유선별공정 모니터링을 위한 다변수 가우시안 혼합모델기반 색상 분석

Froth flotation is a type of mineral processing that selectively separates useful minerals from theBRfroth produced by pulp aeration. The physical features of the froth contain information to understandBRthe status of the process of froth flotation. In particular, by obtaining the color feature of the froth, itBRis possible to predict not only the type of useful mineral but also the grade of the mineral. Therefore,BRit is very important to obtain high-precision color analysis results in froth flotation monitoring. In thisBRpaper, we propose a color analysis method based on multivariate Gaussian mixture models to guaranteeBRthe cyclicity with a period of 360 degrees in hue component of color. In order to verify the proposedBRmethod, we present the color analysis results of images which contain around 0º (360º ) of hue andBRimages obtained by froth flotation. Through the experimental results, it shows that the color analysisBRresults obtained by the proposed method are more precise.BR

Digital image color analysis method to extract fashion color semantics from artworks

Digital image color analysis method to extract fashion color semantics from artworks

Computer vision quantization research on the architectural color of Avenida de Almeida Ribeiro in Macau based on the human eye perspective.

In this study, a new quantifiable and refined urban street color analysis method was proposed by combining professional color cards and efficient software color recognition, which solved the problems of low efficiency and difficulty in the quantification of urban color research and analysis. The research mainly uses China Building Color Card (CBCC) and Python (use programs for the HSV color segmentation of pictures) and other software to carry out color recognition for a street view. From the aspects of color composition, type, proportion, visual level, and color sequence of the street facade, this article makes a quantitative analysis of the color of Avenida de Almeida Ribeiro in Macao from multiple angles. The method of combining color card colorimetry with computer color recognition, which not only considers the inherent color of the building but also includes the color situation under the influence of the environment, can express the “actual color situation” of the building more completely. This article quantifies, combs, summarizes, and compares architectural color and environmental color completely. This method has good universality and ease of use in practice, and the conclusion of the study can provide a reference for the color planning of Macao, the color selection of urban renewal has reference significance, and provide a new method for the study of urban color.

Non-Destructive Prediction of Piperine in Javanese Chilli (Piper Retrofractum Vahl) Based on Color and Texture Analysis Using Artificial Neural Network

Measurement of active substances in herbal plants is currently becoming the major focus of the health industry in Indonesia. Previously, measurement of the active substance had been carried out destructively by extraction methods such as maceration and reflux, which was done by damaged the substrate and required a complicated step. The Artificial Neural Network (ANN), which combined with color and textural analysis methods provides a fast, easy process, does not damage the sample, and minimize errors due to human factors. This study aims to determine and build a relation model between image parameters and the piperine content of Javanese chilli using an optimized ANN with feature selection. The best topology in this study was obtained with an 8-30-40-1 structure (8 inputs, 30 hidden layers 1 node, 40 hidden layers 2 nodes, and 1 output) with a learning rate of 0.1 and a momentum of 0.9; traincgf as a learning function and an activation function of tansig-tansig-purelin. The ANN structure produces a training correlation coefficient (R) of 0.0975, an R validation of 0.9457, a training Mean Square Error (MSE) value of 0.01, and a validation MSE value of 0.0215.

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.

Multilayered Complexity Analysis in Architectural Design: Two Measurement Methods Evaluating Self-Similarity and Complexity

This article contributes to clarifying the questions of whether and how fractal geometry, i.e., some of its main properties, are suitable to characterize architectural designs. This is done in reference to complexity-related aesthetic qualities in architecture, taking advantage of the measurability of one of them; the fractal dimension. Research in this area so far, has focused on 2-dimensional elevation plans. The authors present several methods to be used on a variety of source formats, among them a recent method to analyze pictures taken from buildings, i.e., 2.5-dimensional representations, to discuss the potential that lies within their combination. Color analysis methods will provide further information on the significance of a multilayered production and observation of results in this realm. In this publication results from the box-counting method are combined with a coordinate-based method for analyzing redundancy of proportions and their interrelations as well as the potential to include further layers of comparison are discussed. It presents a new area of box-counting implementation, a methodologically redesigned gradient analysis and its new algorithm as well as the combination of both. This research shows that in future systems it will be crucial to integrate several strategies to measure balanced aesthetic complexity in architecture.

Novel digital assessment technique used to describe peanut nodulation life history

Biological nitrogen fixation (BNF) in legume root nodules is an important source of N globally. Typically, the quantification of BNF is an estimate of N fixation through techniques such as an acetylene reduction assay or isotopic signatures. However, these methods have large logistical limitations, and do not allow for assessments of the nodule morphology or the nodulation process itself, knowledge that is important to fully understand the BNF process. To provide an updated method of nodulation assessments, peanut (Arachis hypogaea L.) nodules were sampled from a two-year field trial and quantified using scanned images of excised nodules, allowing digital assessment of nodule number and size. Further, a digital color analysis method was developed to assess internal nodule color (a known proxy for nodule BNF activity and senescence). To apply and evaluate the new method, peanut nodulation trait data was used for an exploration of the relationship between nodulation traits, plant physiological processes, and nitrogen status in the plant, followed by a nodulation life history analysis. The nodulation assessment method was confirmed by strong correlation with measures of peanut tissue N, biomass, photosynthetic function, and yield. Nodulation life history data suggest novel findings regarding differences in the development of nodules between taproots and lateral roots, contrary to the previous understanding of peanut nodulation life history. This new nodulation assessment method can provide further insight into the BNF process by allowing the collection of detailed data in a relatively simplified manner in field conditions.

Analysis of facial redness by comparing VISIA® from Canfield and CSKIN® from Yanyun Technology.

Redness is the most common symptom among many facial dermatoses. With the rapid development of optical instruments, spectral imaging, and image processing technology, there appear varieties of skin color analysis methods and instruments. The aim of this study is to reveal the differences and correlations in measuring the facial redness between CSKIN® and VISIA® , as well as the relevance between the instrument parameters and clinical evaluation. Forty-three Chinese patients were enrolled. Images were taken and analyzed by VISIA® from Canfield and CSKIN® from Yanyun Technology, and the facial erythema was graded by the dermatologists. Feature counts within the red areas measured by VISIA® were found to have significantly positive correlations with red pixels and percent which were measured by CSKIN® on both sides of the face (r=.45~.566, P<.01). The parameters analyzed by CSKIN® and VISIA® feature counts were correlated with visual scores graded by the dermatologists, VISIA® presented with a weak correlation (r=.213, P<.05), while CSKIN® had a moderate correlation with the visual scores (r=.472~.492, P<.001). CSKIN® may be another alternative option when encountering with measurement and follow-up of facial erythema.

Measurements and monitorings dependent color intensity of drugs and food supplements interactions with textile dyes between TLC plates by using rope printing technique

Pharmacovigilance between drug and food supplements is common in the world and it is important to take precautions before clinical cases In this study interactions between food supplements containing herbal food mixes sweeteners vitamin blends and commonly used painkillers antibiotics and anticoagulants were revealed with helping of macrame ropes smartphone TLC plates and textile dyes and color analysis method supported image j program The sensitivity of the developed method was high LOD ppm LOQ ppm Color analysis results can provide a color risk scale that can be combined with online drug interaction softwares such as Micromedex

Color assessment by different techniques of gilthead seabream (Sparus aurata) during cold storage

Abstract Overall objective of the study was assessment for freshness parameters of gilthead seabream (Sparus aurata). The freshness was determined by two conventional method (i.e. Minolta color measurement method) was compared with a novel machine vision technology (i.e image color analysis method). The quality characteristics related to the freshness of the fresh fish are traditionally based on the color measurements of the whole fish by using Minolta color measurement method. This study aimed to compare the use of the image analysis method to see whether the freshness of seafood can be measured more accurately. Our analysis proved more exact and reliable results in the freshness evaluation of the Sparus aurata based on the color changes in the eyes, gill and skin of the fish. This study revealed that image analysis can be successfully used for the assessment of fish freshness by measuring the color parameters of images captured from skin, gill and eye of the fish during cold storage. It is easy and practical to use image color analysis method in the quality control evaluation of fish freshness measurement. This analysis method can be suitable for use in continuous process at the seafood processing factories (e.g. before packaging to sort out fresh vs old fish automatically).

A Study on the Morphological and Color Analysis Method of Outdoor Advertising - Focusing on the Seoul_Good sign Grand Prize Winner

A Study on the Morphological and Color Analysis Method of Outdoor Advertising - Focusing on the Seoul_Good sign Grand Prize Winner

Segmentation of Myocardium Tissues Using Assembly and Color Analysis Methods

Segmentation of Myocardium Tissues Using Assembly and Color Analysis Methods

A Novel Histochemical Staining Approach for Rare‐Earth‐Based Nanoprobes

AbstractRare‐earth (RE)‐based nanoparticles have exhibited broad potential applications in the biomedical field owing to their unique magnetic and optical properties. But until now, there has been no reliable histochemical staining method developed for probing the distribution of RE‐based nanoparticles in different organs and tissues, which is imperative for evaluating the targeting ability and safety profiles of RE‐based nanoparticles used as the diagnostic probe and the therapeutic agent. Herein, the authors propose a novel and effective staining approach for identifying RE‐based nanoprobes in tissues through unique chromogenic reactions between Chlorophosphonazo III and RE3+, which is independent of the element type. More importantly, a staining color analysis method based on the specific RGB range‐selective integration of the stained images is developed for establishing a quantitative relationship between the optical density and RE3+ concentration in the tissue slices.