Artwork automatic classification is a crucial topic in the field of machine learning, particularly in the context of digitalizing artworks for use in digital museums. Among the various types of artworks, Persian carpets hold a special significance due to their unique patterns, which are crucial in evaluating their craftsmanship and culture value. While Persian carpet is woven in different patterns, the special pattern used in this carpet distinguishes it from other carpet styles such as Chinese, Indian and Turkish carpets. This study focused on the classification of two main Persian carpet patterns, Lachak Toranj and Torkaman, based on quantitative features based on PHOG (Pyramid of Histogram of Orientation Gradients), FFT (Fast Fourier Transform) and saliency map methods. To this end, the grayscale images of 60 carpets with different patterns were collected and the K-means clustering method was used to convert the color of images into the real colors. The PHOG measure was applied to measure anisotropy, self-similarity and complexity features, while the slope of the Fourier transform was employed to extract the unique feature of patterns. Also, a composition feature based on saliency map was introduced for the carpet images classification. According to the results, the anisotropy feature extracted from the PHOG vector has a higher performance for the classification of Persian carpets compared to other features. Also, according to the results the combination of extracted features could be able to the classification of Persian carpet patterns with a 98% accuracy using the Support Vector Machine (SVM) classifier.

ABSTRACT In this paper, a methodology is proposed for uniformly selecting a specified number () of colors for a skin chart from the color solid in CIELAB space under D65/2° viewing condition, based on the ISSA database. The method generates two distinct sets of colors. One set is formed by the centers of equal‐sized cubes, which cover the whole color solid in CIELAB space formed by the ISSA dataset, with each cube containing at least one skin data from the ISSA database. Hence the centers represent skin colors that are uniformly distributed within and around the color solid defined by the ISSA database. Furthermore, reflectance is reconstructed for each of the centers. Another set of colors are the real skin colors from the ISSA database that are nearest to each of the centers. Comparison results show both sets of colors selected by the proposed method outperform the colors selected by the k ‐means and PCA/SVD method using the ISSA database, in terms of color volume and uniformity of distribution within the color solid. Hence, the skin chart developed from colors selected by the proposed method represents the global skin color diversity, and offers potential applications in cosmetics, fashion, printing, photography, and computer vision.

The captured underwater images often have color distortion and blur due to the propagation characteristics of light in water. The enhancement for underwater images using deep learning has shown promising prospect. However, most neural networks model the inputs and outputs end-to-end directly, which fails to fully utilize the inherent information present in underwater images. We focus more on the real color distribution in water that contains comprehensive information, and fully leverage these information to restore the underwater images without the color deviation. In this work, an underwater image enhancement model combining Lab color space and double-opponency mechanism is proposed. Lab color space can extract luminance and chroma, which can express wider chroma range based on human visual perception. Double-opponent mechanism can extract color constancy features based on the biological vision mechanism when the lights have attenuation differences. Moreover, an adaptive light estimation module is designed to learn the light map from the outputs of double-opponency to adjust the overall color of the images. Extensive experiments demonstrate that our approach achieves outstanding results in enhancing color and clarity in underwater images.

Sound–colour synaesthesia is a rare phenomenon in which auditory stimuli automatically evoke stable, subjectively real colour experiences. This study aimed to investigate whether the colours most frequently reported by a synesthete can be reliably predicted based on objective acoustic parameters of voice signals. The study analysed the responses of a 24-year-old blind woman to different voices, which she consciously associates with distinct coloured silhouettes. A classification analysis based on MFCC acoustic feature sets and machine learning algorithms (SVM, XGBoost) demonstrated that the models could be trained with very high Accuracy—up to 97–100% in binary classification and 89–90% in multi-class classification. These results provide new insights into how specific sound characteristics are linked to imagery arising from the human subconscious.

Facial retaining ligaments play a crucial role in maintaining and supporting skin with the superficial musculoaponeurotic system. However, visualizing these ligaments in detail has been challenging due to the limitations of cadaver dissection and radiologic images for plastic surgery. This study aims to visualize and refine the anatomical definitions of the facial retaining ligaments using high-resolution, true-color sectioned images and three-dimensional models. Facial retaining ligaments with their neighboring structures were identified in the sectioned images and reconstructed into 3D models. Using these sectioned images and 3D models, the ligaments were anatomically analyzed alongside neighboring structures. The study revealed distinct morphological features of the retaining ligaments (orbital retaining ligament with the lateral orbital thickening, zygomatic ligament, maxillary ligament, platysma-auricular ligament, masseteric ligament, mental ligament, medial mandibular ligament, mandibular osteocutaneous ligament, cervicomental angle suspensory ligament), including their orientation relative to the skin and their role in anchoring SMAS and adjacent tissues on the real color datasets. These findings enhance our understanding of facial anatomy and offer valuable insights for surgical planning and safer aesthetic procedures. This approach demonstrates the potential of high-resolution anatomical imaging as a superior alternative to traditional dissection and grayscale radiologic imaging.

ABSTRACT A new color gamut for real surface colors is proposed, based on 102 801 samples. This dataset encompasses a diverse range of artificial and natural materials. In order to define this gamut, a modified lattice regression interpolation algorithm was employed to define this gamut. The algorithm effectively balances accuracy and smoothness while maintaining convex hull properties, rendering the proposed gamut suitable for practical applications. A comparative analysis has been conducted between the proposed gamut and a variety of reference color gamuts, including those defined by ISO, Pointer, and the optimal colors. The results demonstrate that the proposed gamut is the most appropriate for the representation of real surface colors. Furthermore, to ascertain the impact of varying lighting conditions and different color spaces, the real surface color gamuts were derived under a range of correlated color temperatures (CCTs), spanning from 2000 to 10 000 K and across diverse color spaces. The findings indicate that the gamut volume initially increases with the increase of CCT, but then gradually and subtly declines when the CCT exceeds approximately 4000 K.

This paper introduces a simple metric for Color Chromaticity Gamut Efficiency (G.E) in terms of color chromaticity in nature. Color Chromaticity Gamut Efficiency is defined as how efficiently a display covers the chromaticity of real objects in nature such as the Standard Object Color Spectra (SOCS) and Pointer's. G.E can be calculated by reproducible area, non‐reproducible area and non‐efficient area regarding real object colors. G.E is higher when the display's color gamut covers ROC efficiently and accurately. Our study found that Adobe + Display P3 has the best color gamut in terms of G.E among various standards including BT.2020. G.E can serve as a guideline for manufacturers when designing display parameters. For instance, a manufacturer might choose to reduce power consumption instead of expanding the color gamut considering G.E. It is expected that consumers could choose a better display with an efficient color gamut, G.E.

We propose a new non-convex first-order variational model for the image super-resolution problem. The model employs a recently developed regularizer that has proven to be effective in image restoration. Due to this regularizer, the salient feature of our model lies in the fact it can construct sharp edges in those generated super-resolution images from lower-resolution ones. Moreover, it also helps suppress the staircase effect. The maximum-minimum principle is proved, which indicates that there is no need to impose hard constraints on the objective function. Alternating direction method of multipliers with spectral penalty selection is utilized to minimize the associated functional. Cartoon and real gray and color images are tested to demonstrate the features of our model to show the comparison with state-of-the-art image super-resolution techniques.

In this study, we take the mural of the Late Tang M1373 tomb unearthed in the eastern suburbs of Xi’an, Shaanxi Province in November 2022 as the object, focus on the insufficient consideration of color authenticity in the current use of image processing for mural visual restoration, as well as the lack of systematic mural color and visual restoration method based on hyperspectral images. A improved spectral recognition method of mural pigment based on fusion spectral analysis and mixed spectral modeling was used in real scene; a virtual restoration method for mural pigment colors based on bandpass energy integration, pseudocolor display and color space correction was proposed; in addition, a integrity restoration of painting patterns including draft line enhancement and human-computer interaction image processing was used in the real mural color restoration. The experimental results show that the mural uses traditional mineral pigments such as ochre, earth yellow, mineral green and carbon black for its red, yellow, green and black pigments, and the accuracy rate of this method is higher than 97% in simulation experiments with noise of %4 spectral amplitude. Meanwhile, the richness of painting color of the restoration results is significantly improved compared to the original color photos, especially, the new method with color space correction is significantly better than the method without color space correction in texture.

The development of single-component white-light emissive phosphors has become a key research area in white light-emitting diode (WLED) technology. However, achieving real color reproduction with an ultrahigh color rendering index (CRI) remains challenging. Herein, a series of 0D hybrid copper halides (TEA)2Cu2Br4- xClx (TEA = tetraethylammonium, x = 0-4) crystals are designed and prepared by a facile solvothermal method. By controlling the composition ratio of Cl- and Br-, the emission spectra are tunable in visible light region from blue to yellow, and a single-component crystal (TEA)2Cu2Br2Cl2 with broadband white-light emission and ultrahigh CRI is obtained. Detailed studies on photophysical mechanism demonstrate that the unique 0D structure of (TEA)2Cu2Br2Cl2 can produce effective emission of self-trapped excitons (STEs), and its dual-band emission phenomenon stems from two STE states in the [Cu2Br2Cl2]2- dimer. Moreover, the CIE coordinates of (TEA)2Cu2Br2Cl2 (0.32, 0.33) are approximated to pure white light (0.33, 0.33), making it an ideal choice for natural WLED applications. A WLED device is fabricated by coating this emitter on a 310nm UV chip, achieving an ultrahigh CRI of Ra = 95 and R9 = 90. This work provides new design principles for developing eco-friendly white-emission phosphors for single-component solid-state WLEDs.

Influence of grape quality tier, harvest timing, and yeast strain on mannoprotein content, phenolic composition, and color modulation in young red wines.

Evidence establishes that there are problems regarding colorimetric coding and standardization of composite resin codes around the world that make the work of clinicians difficult. Determine significant quantitative colorimetric differences (ΔE) in enamel composite resins VITA A2 and A3 respect to VITA-Classical shade, allows clinicians to be alerted to real color differences between products of the same coding. Descriptive in vitro study, 6 resins (N 140) A2 and A3 were used. 7 mm diameter discs, 1 mm (+/-0.1mm) thick were made, measured with spectrophotometry on opaque black background in dark chamber. Values obtained in CIELAB were analyzed obtaining ΔE. ANOVA test of factor 1 (α0.05) was performed. ΔE for products simulating A2 and A3 with respect to Vita-Classical scale was greater than 5 (5= evident instrumental color difference between reference color and obtained color, unacceptable), with exception of A3 FiltekZ350XT (3MESPE, Saint Paul, Minnesota, USA) (3.39±.65) (3 to 4= evident instrumental color difference between reference color and obtained color, but not visually perceptible). There are significant colorimetric differences in enamel composite resins with VITA A2 and A3 coding in studied products, with respect to original VITA-Classical color, when measured spectrophotometer in CIELab with an interval confidence of 95%. All resins are over ΔE 5, meaning that differences between shades are considered clinically unacceptable, with exception of FiltekZ350XT 3MESPE, (3.39±.65) for Vita A3. None of the composite resins meet colorimetric characteristics when compared to Vita-Classical scale, (Bad Säckingen, Germany).

Neural mapping schemes have become appealing approaches to deliver gap-free satellite-derived products for sea surface tracers. The generalization performance of these learning-based approaches naturally arises as a key challenge. This is particularly true for satellite-derived ocean colour products given the variety of bio-optical variables of interest, as well as the diversity of processes and scales involved. Considering region-specific and parameter-specific neural mapping schemes will result in substantial training costs. This study addresses generalization performance of neural mapping schemes to deliver gap-free satellite-derived ocean colour products. We develop a comprehensive experimental framework using real multi-sensor ocean colour datasets for two regions (the Mediterranean Sea and the North Sea) and a representative set of bio-optical parameters (Chlorophyll-a concentration, suspended particulate matter concentration, particulate backscattering coefficient). We consider several neural mapping schemes, and we report excellent generalization performance across regions and bio-optical parameters without any fine-tuning using appropriate dataset-specific normalization procedures. We discuss further how these results provide new insights towards the large-scale deployment of neural schemes for the processing of satellite-derived ocean colour datasets beyond case-study-specific demonstrations.

Currently, the automotive sector is showing increased demands regarding the color of cars in general, but especially the quality and the time of painting, in particular. Companies working in this industry, especially in specialized painting services, must perform work of impeccable quality in the shortest possible time in order to be efficient. Color differences that appear in different areas of the car result from the use of different formulas for obtaining color. These differences can be reduced by using correction factors that are established for the colors in the partial or total painting process of cars. There are several factors that lead to settings that are not verified by the real color and, therefore, contribute to incorrect color results and also to high and unnecessary repair costs. In this study, the authors aimed to optimize the values of the correction factors applicable in the automotive industry, based on a set of 135 measurements performed with a BYK Gardner spectrophotometer, in order to minimize color differences. Through this study, authors have also aimed to find out how the color-identification process can be streamlined with the smallest possible tolerances by optimally adjusting the correction factors and by identifying the factors that influence the color-reading and identification process. A total of 85 pairs of samples were used for the DS1 (data set) and 53 pairs of samples for the DS2 (data set); these samples were used in the visual experiments for testing the performance of two color-differentiation formulas. The first part of the research aimed to investigate the visual perception of the painted cars in terms of differences in brightness, chroma and hue, data that were used to optimize the formulas used for color differences. Finally, authors have estimated the closest color variant to the objective color by optimizing the correction factors and thus achieving the efficiency of the color-identification process and the whole painting-identification process.

Our primary school module with the digital support “Inks” was designed following V.V. Davydov’s idea on the assembling sets context as crucial for number concept formation. Making-sets task and the mixture problem scaffold the initial steps towards proportional reasoning, which is known to be diffi cult for students. The learning situation revolves around purposeful transformations of the inks shade towards the one desired, with a variety of tasks’ conditions: restrictions on the available amount of water and inks, some ready-made mixtures provided, etc. The substantial feature of our instruction was the organization of joint work through distribution of the operations on paint components. The necessity of some preliminary coordination between partners is posed by the real-life restrictions: once water and inks have been mixed, they cannot be separated back. The computer simulation adheres to this “rule” and makes students refer to the special modeling space and plan their operations on water and inks beforehand using tokens. The divergence of results, predicted by students through tokens placement, and the real color shade, obtained in computer simulation, sets the learning task and emphasizes the problem of coordination between partners’ actions within the modeling space. As students start to rely on the portion-by-portion counting, they succeed on the fi rst try: the stain of their new paint, prepared with the different amounts of components, merges with the sample mixture.  second-graders from an urban school (– years old) participated in the experimental teaching series, the video-taped classroom discussions, computer logs and written works were analyzed in order to assess students’ conceptual thinking development. Students’ constant success in tasks and the development of their modeling means functionality proved the computer support, which we have designed, to be relevant in several aspects: problematization and feedback, enabling simultaneous partners’ work, providing substantial tasks variations

The fetal venous system begins developing around the sixth week of gestation, with three paired veins: the umbilical, vitelline, and cardinal veins. These veins are essential for transporting blood from the placenta to the heart. As the liver matures, connections between the liver and these veins form a complex venous system. Disruptions in this process can lead to various fetal venous anomalies, arising from abnormalities in the formation or regression of these veins. Common anomalies include ductus venosus agenesis, persistent right umbilical vein, umbilical vein varix, agenesis of the portal system, and IVC interruptions. Ductus venosus agenesis can cause compensatory blood flow changes, while a persistent right umbilical vein occurs when the left vein regresses. Umbilical vein varix is a dilation of the umbilical vein, and agenesis of the portal system disrupts normal liver blood flow. IVC interruptions affect systemic venous return to the heart. Diagnosing these anomalies requires detailed ultrasound evaluation, including Doppler studies, and prenatal monitoring to assess potential complications and guide appropriate clinical management. In evaluating complex communication pathways, the first step is to examine how that structure is organized. The categorized segmentation of the venous system leads to a wider horizon of vision and higher perception. In this pictorial essay article, the fetal venous system and its anomalies are classified according to their primary origin. Special attention to depicting normal anatomy and anomalies using color schematic images and real two-dimensional and color ultrasound images together play an important role in promoting spatial perception and simplifying the categorized approach to fetal venous system anomalies.

This article focuses on TikTok social media that uses AI (Artificial intelligence) technology to visualize video content. In this day and age, technology is increasingly sophisticated, one of which is AI technology which plays a major role in creating content in a short time. One of the unique concepts of using AI (artificial intelligence) is the balance to attractively visualize each object in the image. This technology can also edit and create content in the form of videos, images, illustrations, etc. The use of AI in visual communication in video content has a great effect on creating visual aesthetics to be more beautiful and have real color contrasts, and can also provide information with the video without having to use words. This research will also look at the technical description of how AI (Artificial Intelligence) can provide great benefits in providing information through video visualization. To achieve this goal, the researcher uses a qualitative approach method with phenomenology in order to get a comprehensive picture of the object of research. The role of AI in visual communication is expected to provide great benefits and apply it properly through creativity and innovation that comes from human ideas to create interesting images or videos.

Typically the sensitivity V2 (λ) for a 2° standard observer is used at photometric measurments. Nevertheless, the light reach the human eye from wider field of view. This fact motivated the International Commission on Illumination to introduce the 10° supplementary observer with sensitivity V10 (λ). This paper analyzes the impact of transition from V2 (λ) to V10 (λ) on measured pc-LEDs illuminance values. The results indicate that the maximum difference is 2% for 3000 K pc-LEDs, 4% for 4000 K pc-LEDs, and 6% for 6500 K pc LEDs. Full Text: PDF References K.S. Gibson, E.P.T. Tyndall, "Visibility of Radiant Energy", Scientific Papers of the Bureau of Standards, 19, 131 (1923). CrossRef E.P. Hyde, W.E. Forsythe, F.E. Cady, J. Frank. "The visibility of radiation", Inst. 185, 829 (1918). CrossRef I. Fryc, M. Listowski, R. Supronowicz, "Going beyond the 20th century color space to evaluate LED color consistency", Opt. Express 31(23), 38666 (2023). CrossRef R. Supronowicz, J. Fan, M. Listowski, A. Watras, I. Fryc, "Application of different metrics for describing light color quality of white LED", Photonics Lett. Pol 13, 32 (2021). CrossRef W.S. Stiles, J.M. Burch, "N.P.L. Colour-matching Investigation: Final Report (1958)", Optica Acta: Int. J. Opt. 6, 1 (1959). CrossRef CIE 165:2005 CIE 10 Degree Photopic Photometric Observer, (2005). DirectLink J. Nathans, D. Thomas, D.S. Hogness, "Molecular Genetics of Human Color Vision: The Genes Encoding Blue, Green, and Red Pigments", Science 232, 193 (1986). CrossRef A. Roorda, A.B. Metha, P. Lennie, D.R. Williams, "Packing arrangement of the three cone classes in primate retina", Vis. Res. 41, 1291 (2001). CrossRef H. Hofer, J. Carroll, J. Neitz, M. Neitz, D.R. Williams, "Organization of the Human Trichromatic Cone Mosaic", J. Neurosci. 25, 9669 (2005). CrossRef C.A. Curcio, K.R. Sloan, R.E. Kalina, A.E. Hendrickson, "Human photoreceptor topography", J. Comp. Neurol. 292, 497 (1990). CrossRef D. Mustafi, A.H. Engel, K. Palczewski, "Structure of cone photoreceptors", Prog. Retin. Eye Res. 28, 289 (2009). CrossRef E.M. Wells-Gray, S.S. Choi, A. Bries, N. Doble, "Variation in rod and cone density from the fovea to the mid-periphery in healthy human retinas using adaptive optics scanning laser ophthalmoscopy", Eye 30, 1135 (2016). CrossRef S. Bara, M.A. Bonmati-Carrion, J.A. Madrid, M.A. Rol, "Multispectral estimation of retinal photoreceptoral inputs", Photonics. Lett. Pol 11, 60 (2019). CrossRef CIE 170-2:2015 Fundamental Chromaticity Diagram With Physiological Axes - Part 2: Spectral Luminous Efficiency Functions And Chromaticity Diagrams, (2015). DirectLink I. Fryc, T. Dimitrova-Grekow, "An automated system for evaluation of the quality of light sources", 2016 IEEE Lighting Conference of the Visegrad Countries (Lumen V4) (2016). CrossRef I. Fryc, "Spectral correction of a detector used in illuminance measurements", Proc. SPIE 3820, 343 (1999). CrossRef H. Wright, C.L. Sanders, D. Gignac, "Design of Glass Filter Combinations for Photometers", Appl. Opt. 8, 2449 (1969). CrossRef S. Winter, D. Lindner, A. Sperling, G. Sauter, S. Brown, T. Larason, Y. Zong, Y. Ohno, Proceedings of the 9th International Conference on New Developments and Applications in Optical Radiometry (NEWRAD), Davos, 2005. DirectLink I. Fryc, P. Tabaka, "The influence of different photometric observers on luxmeter accuracy for LEDs and FLs lamps measurements", Opt. Appl. XLIX, 345 (2019). CrossRef U.S. Energy Information Administration, Commercial Buildings Energy Consumption Survey (2021). DirectLink United Nations Environment Programme (2013). Minamata convention on mercury: text and annexes, (2013). DirectLink M. Listowski, R. Supronowicz, "Color quality consideration when switching from FL to LED", Photonics Lett.Pol. 14, 56 (2022). CrossRef J. Cho, J.H. Park, J.K. Kim, E.F. Schubert, "White light-emitting diodes: History, progress, and future", Phot. Rev. 11, 1600147 (2017). CrossRef K. Bando, K. Sakano, Y. Noguchi, Y. Shimizu, "Development of High-bright and Pure-white LED Lamps", J. Light & Vis. Env. 22, 2 (1998). CrossRef M. Listowski, "Porównanie modelowanych oraz rzeczywistych wartości parametrów świetlnych i kolorymetrycznych białych diod LED pracujących w szerokim zakresie temperatur", Przegląd Elektrotechniczny 1, 59 (2022). CrossRef W. Song, D. Durmus, "Evaluating Energy Efficiency and Colorimetric Quality of Electric Light Sources Using Alternative Spectral Sensitivity Functions", Buildings 12, 2220 (2022). CrossRef S. Jost, A. Thorseth, T. Poikonen, P. Blattner, T. Gerloff, A. Kokka, P. Dekker, M. Smid, A. Ferrero, T. Kubarsepp, P. Gal, S. Källberg, A. Klej, G. Brida, T. Reiners, K. Ludwig, M. Schneider, L. Hui, EMPIR 15SIB07 PhotoLED - Database of LED product spectra, (2021) CrossRef M. Royer, Real Light Source SPDs and Color Data for Use in Research, (2023). CrossRef ANSI C78.377 Electric Lamps - Specifications For The Chromaticity Of Solid-State Lighting Products, (2017). CrossRef Y. Ohno, "Practical Use and Calculation of CCT and Duv", LEUKOS 10(1), 47 (2014). CrossRef

Due to the high flexibility and remarkable performance, low-rank approximation has been widely studied for color image denoising. However, existing methods usually ignore the cross-channel difference or the spatial variation of noise, which limits their capacity in the task of real world color image denoising. To overcome these drawbacks, this paper proposes a double-weighted truncated nuclear norm minus truncated Frobenius norm minimization (DtNFM) model, and apply it to color image denoising through exploiting the nonlocal self-similarity prior. The proposed DtNFM model has two merits. First, it models and utilizes both the cross-channel difference and the spatial variation of noise. This provides sufficient flexibility for handling the complex distribution of noise in real world images. Second, the proposed DtNFM model provides a close approximation to the underlying clean matrix since it can treat different rank components flexibly. To solve the DtNFM model, an efficient algorithm is devised through exploiting the framework of alternating directions method of multipliers (ADMM). Meanwhile, the truncated nuclear norm minus truncated Frobenius norm regularized least squares subproblem is discussed in detail, and the results show that its global optimum can be directly obtained in closed form. Therefore, the DtNFM model can be efficiently solved by a single ADMM. Rigorous mathematical derivation proves that the solution sequences generated by our proposed algorithm converge to a single critical point. Extensive experiments on synthetic and real noise datasets demonstrate that the proposed method outperforms many state-of-the-art color image denoising methods. MATLAB code is available at https://github.com/wangzhi-swu/DtNFM.

Oral photography is one of the essential methods of maintaining dental records. The primary purpose of photography is to record an image. Images of the oral cavity should have sufficient detail for discerning the features of the hard and soft tissues; in addition, they should accurately reproduce the real colors as they appear in the mouth. Photographs are of value during the repeated monitoring of patients and while making comparisons among historical cohort studies. This article describes the equipment and techniques for obtaining high-quality images of the oral cavities of dogs and cats in a standardized way.