Color Regions Research Articles

Innovative synthesis and forensic applications of bio-mediated SrO–MgO–In[formula omitted]O[formula omitted] nanocomposites with blue photoluminescence

The first of its kind Strontium oxide–Magnesium Oxide–Indium oxide (SMI) nanocomposites were synthesized utilizing a bio-mediated method with Euphorbiatirucalli latex as a reducing agent, followed by calcination. Synthesis of SMI NCs is confirmed by Bragg reflections of SrO, MgO, and In2O3, among them peaks belonging to In2O3 are observed to be prominent. The crystallite size, and other parameters like dislocation density, strain, structural factor, and crystallinity were estimated. Due to lower surface energy and the adhesion of particles with weak forces, morphology of the surface contains a larger degree of agglomeration. The direct energy band gap was determined to be 3.18 eV. Furthermore, the PL (photoluminescence) emission spectra, CIE, and CCT coordinates strongly indicate high-intensity emission in the region of blue color. Dusting of powder reveals latent fingerprints. Synthesized SMI nanocomposite exhibits highly-resolved patterns in the form of ridges used to analyze specific latent fingerprints with clarity. Thus, the recently synthesized nanocomposite may have been used in forensics, fluorescence labeling, and blue light emission.

Two-stage deep image restoration network with application to single image shadow removal

In this paper, we introduce a two-stage deep learning-based image restoration network and its application to remove shadow information from a single image, named by ESCNet (Encoder-decoder based Shadow removal with Colorization Network). Most existed single image-based shadow removal methods may suffer from that the shadow contains multiple regions of different colors or rich image details. To tackle with the problems, our key idea is to first remove shadow(s) from an image followed by repainting the shadow-removed region(s) in this image. To accomplish this, we present a deep two-stage network, cascading a shadow removal network (SRN) and a colorization network (CN). The presented encoder-decoder-based SRN with fusion of global and local feature information is used to remove the shadow(s) in the grayscale domain of the input image while recovering the image details for the shadow-removed region(s). Then the proposed CN aims at repainting the removed shadow region(s) via re-colorization. The proposed deep model has been well trained and well evaluated on the two well-known public datasets, i.e., ISTD (Image Shadow Triplets Dataset) and SRD (Shadow Removal Dataset). Experimental results have shown that the proposed method outperforms the compared state-of-the-art (SOTA) shadow removal approaches quantitatively and qualitatively.

Research on Image Colorization Based on Deep Learning

Abstract Gray scale picture colorization, a research hotspot in the domain of computer vision, seeks to assign reasonable colours to every single pixel of a grayscale picture, enriching the visual information of the coloured picture. Neural networks take grayscale images as input and output colorized images. From a psychological perspective, colours can provide observers with a more pleasant perceptual experience. Old photos can also be coloured, which are important documentary resources for recording real history and restoring the social landscape of the time. Additionally, due to the limitations of imaging mechanisms, most medical images are grayscale. Therefore, research on grayscale image colorization is a task of significant importance. However, existing automatic image colorization systems have issues such as “blurry boundaries”, “colour overflow”, “inappropriate colour choices” and “incorrect colour regions”. This paper proposes a model combining adversarial neural networks and U-Net networks, optimizing them by incorporating global feature fusion modules, Pathway emphasis mechanisms and spatial focus mechanisms. The idea of Markov discriminator was added to the discriminator, and the loss function was optimized. The ultimate investigative conclusions demonstrate that the PSNR and SSIM of the suggested system are 24.45 and 0.941, accordingly, in relation to the preceding protocol, which are 3% and 5% higher than the previous algorithm, and the example has been ameliorated to some degree. And the loss function is modified, and the final algorithm can improve the effect of picture colouring, which encompasses a broad spectrum of application prospects.

Video, Feminism and Television: A Trajectory of the Brazilian Feminist Collective Lilith Video, 1983–1988

This article examines the television work made by Lilith Video (1983–1988), active in the city of São Paulo, and one of the first feminist video collectives in Brazil. Lilith was founded by Jacira Melo, Márcia Meireles, and Silvana Afram, producing documentaries and the unprecedented Feminino Plural, a series of five episodes, each one focused on an aspect of the everyday life of Brazilian women. In 1987, TV Cultura public television broadcast the series twice. Feminino Plural still remains perhaps the only feminist programme ever made by an independent collective to go on air. We start by situating the works of the group within Brazilian and international literature; we highlight the ways in which its history interweaves video art, television production, and feminist social movements in immediate Brazilian post-dictatorship. As we move to the analysis of the series, we discuss how the combination of testimony, dramatization, archive, and voice over allowed for a sensible approach to private issues in the virtual public space. By mapping Feminino Plural’s intersectional connections, this article suggests the ways in which the series helped to expand the scope of what was possible for women, understood as plural, opened to colour, class, age, and geographic regions.

Modeling the Color Characteristics of Sapphires through the Statistical Method and Function Simulation Method

The aim of this study was to explore the feasibility of quantitatively evaluating a sapphire’s color by analyzing gemstone images. The color characteristics of gemstones through photography and color extraction were accurately captured, and the key color parameters for different color regions of gemstones were extracted. Then, the color of sapphires was simulated by statistical method and function simulation method. The results indicate that the brightness value of the bright area was the highest and the chroma value of the “fire” area was the highest. The chroma (C) of the sapphires was linearly positively correlated with the absolute value of its b value, and the brightness (L) showed a quadratic correlation with its chromaticity parameters (b or C). The function simulation method with an average of b as the main independent variable had a larger standard deviation, which proves that this method has a stronger ability to distinguish the differences in a sapphire’s color. This method can be extended to the color evaluation of other colored gemstones, and it can be used to form a gemstone color evaluation system.

Structural, optical and luminescent properties of Tm3+-doped phosphate oxyfluoride glasses for blue emission solid state devices

In this work, the visible luminescence of P2O5-KF-Al2O3 glasses with Tm2O3 was studied. The Tm3+ ion can have a strong blue emission, which allows the development of LEDs in this color region. This study refers to the synthesis of oxyfluorophosphate glasses, 38P2O5+(50-x)KF+12Al2O3+xTm2O3 (PKAl:Tm), with x = 0.25, 0.50, 0.75, and 1.00 mol%, by the melt-quenching method. The prepared materials showed amorphous characteristics verified by XRD data. The absorption spectra shown six main bands characteristic of Tm3+ ions, from ground state 3H6 to excited levels 3F4, 3H4, 3H5, 3F3,2, 1G4 and 1D2, in which the intensities increased with the concentration of Tm2O3. In the FTIR spectra, it was verified that the profiles of the PKAl samples are similar to glasses based on phosphate systems. The Judd-Ofelt parameters were calculated, where for PKAl glasses the trend was Ω2>Ω4>Ω6. The excitation spectra of PKAl:Tm glasses shown an intense band centered at 358 nm (3H6→1D2). The luminescence spectra with excitation at 358 nm shown two bands at 453 nm (1D2→3F4), and 480 nm (1G4→3H6); the highest emission intensity was observed to the sample doped with 0.75 mol% of Tm2O3. The calculated CIE diagram shown that the doped samples have coordinates close to the primary blue color, which favors the application for the development of blue LEDs and wLEDs. The decay curves for the 1D2 level were fitted by single exponential with lifetime values decreasing with increasing concentration of Tm2O3. These results show that the PKAl:Tm glasses are potential candidates for applications in LEDs.

Luminescent properties of Tm3+-activated phosphors with rosiaite structure

A series of solid solutions with compositions of La1-xTmxGa0.5Sb1.5O6 (x = 0.03, 0.05, 0.1) and La1-x-y-zTmxTbyDyzGa0.5Sb1.5O6 (x = 0.04, 0.07, 0.1; y = 0.04, 0.07, 0.1; z = 0.04, 0.04, 0.06) has been synthesized. It is shown that all the compounds have rosiaite structure (PbSb2O6, sp.gr. P-31m). Morphology, spectral-luminescent characteristics and color coordinates of the samples were studied. It was found that luminescence spectrum of thulium-activated samples recorded upon 351 nm excitation is typical for Tm3+ ions. At the same time, under excitation by radiation with λ = 457 nm and a power density of J = 4.7 kW/cm2, broadband thermal emission is observed, against which the bands corresponding to the 1G4→3H6, 1G4→3F4, 3F4→3H6 и 3H4→3H6 transitions of Tm3+ are detected. The luminescence spectra of the samples co-activated with Tm3+, Tb3+ and Dy3+are characterized by a relatively low intensity of the Tm3+ emission, which may be due to efficient energy transfer processes between Tb3+ and Dy3+ ions. A shift from the blue to the green color regions is observed in the color coordinates of the co-activated samples upon 351 nm excitation. Radiation with λ = 457 nm led to a shift in the emission colour to orange. Thus, it is shown that it is possible to create phosphors emitting in the blue, green and orange spectral regions by changing the wavelength of exciting radiation and activator composition for compounds with rosiaite structure.

The effect of Al3+ ions on the self-reduction process of Yb3+ to Yb2+ ions and optical properties of Nd3+/Ybn+ (n = 3, 2) co-doped transparent silicate glass-ceramics containing Ba2LaF7 nanocrystals and Ag nanoparticles

The effect of Al3+ ions in the AlF3 compound on the reduction process of Yb3+ to Yb2+ ions in SiO2–AlF3–BaF2–TiO2–LaF3 (SABTL) transparent silicate glass-ceramics was investigated. The valence states of the elements in the raw materials mixture existing in the transparent silicate glass-ceramics were determined using X-ray photoelectron spectroscopy (XPS) spectrum analysis. The transparent silicate glass-ceramics SABTL containing Ba2LaF7 nanocrystals and Silver (Ag) nanoparticles (AgNPs) were identified through X-ray diffraction (XRD) analysis and transmission electron microscopy (TEM) image. With the increase of Al3+ ions molar concentration, the self-reduction process of Yb3+ to Yb2+ ions was enhanced and thus significantly affected the optical bandgaps and upconversion (UC)-, near-infrared (NIR)- emissions of Nd3+/Yb3+ co-doped in SABTL containing Ba2LaF7 nanocrystals and AgNPs under excitation of 980 nm laser diode (LD). The optimal molar concentration ratio between SiO2 and AlF3 compound was determined such that the NIR bandwidth flatness of Nd3+/Yb3+ co-doped in SABTL containing Ba2LaF7 nanocrystals in the wavelength range of 1000–1200 nm was the flattest. In addition, the CIE 1931 (x, y) color coordinates for UC- and visible (VIS)- emissions of Nd3+/Yb3+ co-doped SABTL-0.5Nd2Yb-xAg (x = 0, 2, 3, 4, and 5) glass-ceramics samples are also calculated and determined the color region for light-emitting diode (LED) application.

Reference Image Aided Color Matching Design Based on Interactive Genetic Algorithm

This paper proposes an interactive genetic algorithm to assist designers in color selection and match different color combinations extracted. Then, based on the CorelDraw development environment, this paper establishes a graphic-based man-machine dialogue model. Through simulation experiments, genetic algorithms such as random selection, hybridization, variation, color region adjustment, etc. Finally, the best color combination is obtained and combined with the image. Within the scope of color extraction value, designers can use interactive genetic algorithm rules to view color planning from a holistic perspective. Under the influence of human-computer interaction, each scheme is optimized step by step, so that the color ideas matching the designer can be found quickly.

AN EFFICIENT IMAGE PROCESSING BASED IMAGE TO CARTOON GENERATION BASED ON DEEP LEARNING

This paper proposes an approach to convert real life images into cartoon images using image processing. The cartoon images have sharp edges, reduced colour quantity compared to the original image, and smooth colour regions. With the rapid advancement in artificial intelligence, recently deep learning methods have been developed for image to cartoon generation. Most of these methods perform extremely huge computations and require large datasets and are time consuming, unlike traditional image processing which involves direct manipulation on the input images. In this paper, we have developed an image processing based method for image to cartoon generation. Here, we perform parallel operations of enhancing the edges and quantizing the colour. The edges are extracted and dilated to highlight them in the output colour image. For colour quantization, the colours are assigned based on proposed formulation on separate colour channels. Later, these images are combined and the highlighted edges are added to generate the cartoon image. The generated images are compared with existing image processing approaches and deep learning based methods. From the experimental results, it is evident that the proposed approach generates high quality cartoon images which are visually appealing, have superior contrast and are able to preserve the contextual information at lower computational cost.

Grinding Surface Roughness Measurement Combined with Simulation Data and Transfer Learning

AbstractThe surface‐roughness machine vision measurement method requires training numerous samples with uniform roughness values to construct a prediction model. Insufficient actual sample size will make the model lack generalization ability. So, a grinding surface‐roughness measurement method combined with simulation data and transfer learning is proposed. First, through surface simulation, inverse fitting, and three‐dimensional (3D) modeling, more realistic simulation samples are obtained, real samples are prepared, and a simulation imaging system and an actual imaging experiment to acquire surface images are designed. Second, the data distribution difference between the simulation domain and the actual domain through transfer component analysis and the use of the adjusted simulation‐domain data and its label to train a support vector regression model is adjusted. Finally, the model predicts the surface roughness of the uncalibrated actual‐domain sample. For shared features of transferable simulation images and actual images, using the high sensitivity of color information, image features are enhanced and a proportion of pure color region index is designed, strongly correlated within the domain but less differentiated between domains. The results show that the transfer learning prediction accuracy based on this index exceeds 90%, verifying the feasibility of the proposed method and providing a new improvement strategy for sample expansion in visual roughness measurement.

Dorsal and Ventral Plumage Coloration Evolve as Distinct Modules with Different Environmental Correlations.

AbstractMany animals exhibit contrast between their dorsal coloration and their ventral coloration. If selection acts differently on dorsal versus ventral coloration, ancestral covariance between these traits should break down, eventually leading to independent modules of trait evolution. Here, we compare the evolution of feather color across body regions for a clade of Australasian songbirds (Meliphagoidea). We find evidence for three modules of covarying color regions. Among these modules, ventral feathers evolve with high lability, evolving at three times the rate of dorsal plumage and 20 times the rate of flight feathers. While both dorsal plumage and ventral plumage are darker in areas with more precipitation and vegetation, we find that dorsal plumage is twice as similar to colors in satellite photos of background substrates. Overall, differential selection on ventral and dorsal colors likely maintains these as distinct modules over evolutionary timescales-a novel explanation for dorsoventral contrast in pigmentation.

Research on innovative visualization design of miao costume images in Qiandongnan under aesthetic perspective

Abstract In this paper, we take the images of Miao costumes as the research object, construct the color system of Miao costumes based on the aesthetics perspective, and take the color migration as the research content to realize the visualization and innovative design of Miao costumes. Firstly, typical Miao dress images are obtained by digital acquisition. Then, RGB and HSL color modes are used to extract the colors and mine the color association rules of Miao dresses to construct the color system of Miao dresses. Then, an image segmentation method based on the color system of Miao costumes is proposed to achieve color migration between the color regions of decorative patterns. Finally, the patterns in the dataset of Miao costumes in Qiandongnan are extracted. Based on the classification study, a systematic and in-depth analysis of the color performance of the pattern patterns is conducted to clarify their artistic and aesthetic forms. It is found that the colors of Qiandongnan Miao costume patterns are mostly high-purity and high-brightness colors, of which high-purity colors (7-10) account for the highest proportion, including 16 colors such as earth red, grape purple, pink, and big red, accounting for about 56.5% of the total. The proportion of high brightness colors (7-10) in the colors is the highest, including 13 colors such as beige, goose yellow, grape purple, peach red, etc., accounting for 68.1%. It can be seen from the use of hues in the dress patterns of the Miao people in Qiandongnan that they will match the colors of the patterns according to the “five colors” and highlight a certain color as the dominant color according to the theme. The whole is complete, full of variegated and strong ethnic flavor.

Region-Aware Color Smudging.

Color smudge operations from digital painting software enable users to create natural shading effects in high-fidelity paintings by interactively mixing colors. To precisely control results in traditional painting software, users tend to organize flat-filled color regions in multiple layers and smudge them to generate different color gradients. However, the requirement to carefully deal with regions makes the smudging process time-consuming and laborious, especially for non-professional users. This motivates us to investigate how to infer user-desired smudging effects when users smudge over regions in a single layer. To investigate improving color smudge performance, we first conduct a formative study. Following the findings of this study, we design SmartSmudge, a novel smudge tool that offers users dynamical smudge brushes and real-time region selection for easily generating natural and efficient shading effects. We demonstrate the efficiency and effectiveness of the proposed tool via a user study and quantitative analysis.

Systematic Search for Water Fountain Candidates Using the Databases of Circumstellar Maser Sources

Water fountains (WFs) are thought to be objects in the morphological evolution of the circumstellar envelopes of low- and intermediate-mass evolved stars, transitioning from spherically symmetric to asymmetric shapes. We used databases of circumstellar 1612 MHz OH and 22.235 GHz H2O maser sources to search for new WF candidates using the criterion of a larger velocity range of the H2O maser emission compared to that of the OH maser emission. Thus, it is in principle possible to identify WFs with H2O velocity ranges smaller than those for the previously known WFs. For the OH maser line, we analyzed database entries of 8474 observations from 2195 sources, and 6085 observations from 3642 sources for the H2O maser line. After a close examination of the velocity ranges and line profiles, we identified 11 sources that meet the criterion mentioned above. We examined the IRAS colors of the selected sources and found that two of them (IRAS 19069+0916 and IRAS 19319+2214) are in the color region for post-AGB stars. We find that the maser velocity criterion can discover other astrophysically interesting objects than just WFs. Such objects may include peculiar planetary nebulae with maser emissions and stellar merger remnants.

СОВЕРШЕНСТВОВАНИЕ АЛГОРИТМА МАШИННОГО ЗРЕНИЯ В БИОТЕХНИЧЕСКИХ СИСТЕМАХ С ПРИМЕНЕНИЕМ НЕЙРОННЫХ СЕТЕЙ

A review of the hardware design of machine vision systems is given in the work; the basic principles of image processing of biotechnical systems and the corresponding mathematical apparatus are considered using the example of the use of machine vision technology in digital dermatoscopy. The digital information extracted by the computer vision system is transferred to special software for image processing using machine learning methods, among which the work highlights the following: neural networks, regression, classification, and object detection. A classification of neural networks that are used for computer vision is given and a brief description of their practical application is given. The considered methods of computer vision systems in biotechnological practice using convolutional neural networks open up opportunities for improving the quality of visual diagnostics. A comparison with previously known methods for classifying digital objects was carried out in the work to analyze the effectiveness of using CNN. Analysis of the digital object by a convolutional neural network using the Statistica software package revealed different color regions. The accuracy of classification of areas of a digital object was 94.7%, which indicates a high accuracy of digital object recognition using CNN and is 1.5% more accurate than statistical classification methods.

Visual complexity of urban streetscapes: human vs computer vision

Understanding visual complexity of urban environments may improve urban design strategies and limit visual pollution due to advertising, road signage, telecommunication systems and machinery. This paper aims at quantifying visual complexity specifically in urban streetscapes, by submitting a collection of geo-referenced photographs to a group of more than 450 internet users. The average complexity ranking issued from this survey was compared with a set of computer vision predictions, attempting to find the optimal match. Overall, a computer vision indicator matching comprehensively the survey outcome did not clearly emerge from the analysis, but a set of perceptual hypotheses demonstrated that some categories of stimuli are more relevant. The results show how images with contrasting colour regions and sharp edges are more prone to drive the feeling of high complexity.

WS2 incorporated PANI-rGO nanocomposites tailored for inflated thermal, optical and electrical properties used as ETL for OLEDs

This work reports on the synthesis of polymeric PANI-rGO-WS2 (PGW) nanocomposites were synthesized with varying concentrations of WS2 via chemical oxidative polymerization. FESEM images elucidated that the surface morphology of PGW3 carried a structure comprising of PANI nanofibers embedded on the top of the overlapped rGO and WS2 nanosheets. XRD and FTIR spectroscopy showed the molecular interaction among the constituents and affirmed the formation of PGW nanocomposite. UV–Vis. spectroscopy revealed the absorption of light in visible region with the for PGW3 nanocomposite. Photoluminescence spectroscopy showed light absorption in blue color region with excellent color purity. TGA showed the optimized PGW3 nanocomposite has inflated thermal stability. Current density for PGW3 nanocomposite was examined using J-V characteristic curve and found 96% higher than polyaniline. The increased conductivity and high electron-hole recombination rate attributed to the formation of enhanced charge transport network in PGW3 nanocomposite. These results evinced the optimized PGW3 nanocomposite as an ETL for OLED applications.

Insight into the photoluminescence and morphological characteristics of transition metals (TM = Mn, Ni, Co, Cu)-doped ZnO semiconductor: a comparative study

In this work, undoped and transition metal (TM = Mn, Ni, Co, Cu)-doped ZnO thin films were grown on Si substrate using the ultrasonic spray pyrolysis technique, adhering to the same deposition conditions to compare their morphological and photoluminescent characteristics. X-ray Photoelectron Spectroscopy (XPS), Atomic Force Microscopy (AFM), and Photoluminescence (PL) spectroscopy were used to investigate the chemical composition, morphology, and luminescence properties, respectively. XPS results indicate that Mn and Ni ions have bivalent and trivalent electronic states coexisting in the ZnO lattice, Cu ions have both monovalent and bivalent states, and Co ions have only bivalent states. Besides, there is a considerable increase in the level of oxygen vacancies observed upon TM doping. The topographic and phase-contrast AFM images, supported by their associated statistical parameters and mean height distribution histograms, reveal that TM doping increases the tendency for crystalline grains to coalesce in 3D, resulting in a more roughened surface, larger grains with prominent boundaries, increased porosity, and an inhomogeneous height distribution. PL spectra of TM-ZnO show a broadening of the ZnO band gap accompanied by different luminescence behavior compared to pure ZnO regarding both UV and visible emissions. CuZnO is characterized by a green luminescence, CoZnO and MnZnO by a red luminescence, and ZnO and NiZnO by a broad visible luminescence. The possible mechanism for defect luminescence in each TM-ZnO sample was systematically investigated. The chromaticity color coordinates of the PL emissions show that the films provide different color regions well distributed on the CIE chromaticity diagram. The findings regarding the coexistence of two valence states of TM doping, the level of oxygen vacancies, the grain coalescence process, and the luminescence characteristics are carefully correlated and discussed herein.

Crowd counting algorithm based on face detection and skin color recognition

This paper introduces an innovative crowd counting algorithm using skin color information. Through stages of color space transformation, threshold segmentation, morphological processing, and region filtering, the algorithm successfully conducts crowd counting in images. The study encompasses analyses of images with diverse crowd densities, skin colors, backgrounds, and lighting intensities, revealing the algorithm's robustness to various factors. It remains unaffected by skin color and crowd size and exhibits minimal sensitivity to background and lighting intensity. Furthermore, the paper explores image feature analysis and uses MATLAB programming for simulation and initial crowd counting, considering images with different actual crowd sizes. Despite minor issues such as the insufficient separation of faces from clothing and the influence of lighting intensity, the algorithm performs reliably in most scenarios, demonstrating high crowd counting accuracies. To bolster the accuracy and robustness of the algorithm, optimization of the separation step and control of the lighting effect on images is suggested. The key focus of this study is the application of the Gaussian model in the YCbCr color space for face detection and examining its impact on the efficiency and accuracy of crowd counting algorithm. The research not only provides a novel approach for crowd counting in images but also offers insightful perspectives for future studies and potential improvements. Thus, the study proves to be a significant contribution to face detection and recognition technology, enhancing its application in fields like public safety, crowd management, and surveillance systems.