Color Harmony Research Articles

Urban Architectural Color Evaluation: A Cognitive Framework Combining Machine Learning and Human Perception

Architectural color significantly impacts the quality of built environments and is closely related to the physical and mental health of residents. Previous studies have conducted numerous valuable explorations in this field; however, the challenge of quantitatively measuring the characteristics of architectural colors in depth and examining the complex relationship between these colors and human perception remains an unresolved issue. To this end, this study builds upon recent advancements in data technology and emotion analysis to develop a comprehensive cognitive framework for urban architectural color evaluation. It combines machine learning techniques and perception scales, utilizing both objective and subjective data. By acquiring and recognizing numerous street-view images of the Changsha Central District, we quantitatively examined the hue, saturation, value, color complexity index and color harmony index of urban architectural colors and investigated the complex relationships between human perception and architectural colors through large-scale participant ratings and correlation analyses. The results show that the architectural colors of the study area are warm, with low saturation and moderate value. Most areas exhibit a high color complexity index, whereas the overall color harmony score is low. Human-perception evaluations indicate that people are generally satisfied with the urban architectural colors of the Changsha Central District. For further optimization, the saturation and color harmony scores need to be enhanced. This study provides a comprehensive evaluation of urban architectural color quality, visualizing the complex relationship between urban architectural color and human perception. It offers new perspectives for improving the built environments and supporting sustainable development, with practical application value.

Application of colour theory and visual merchandising principles in retail spaces

In retail settings, the strategic application of color theory and visual merchandising concepts is essential for influencing customer perception and increasing sales. One of the most obvious visual cues, color has a significant psychological impact on consumers, affecting their mood, perception, and buying habits. Retailers can create aesthetically pleasing spaces that suit their brand identity and client preferences by utilizing color theory concepts like complementary colours, warm versus cold tones, and color harmony. For instance, cool hues like blue and green express serenity and trust, while warm hues like red and yellow are frequently employed to convey a sense of urgency and enthusiasm. The creative placement of goods and displays to maximize consumer interaction and promote sales is known as visual merchandising. The utilization of contrasts, lighting, focal points, and product placement are important guidelines. Together with color theory, these components produce an engaging shopping experience that improves product visibility, makes navigating the store easier, and leads shoppers through it with ease. In addition to drawing in new clients, the strategic use of color psychology and visual merchandising strategies also affects their purchasing habits, increasing sales and building brand loyalty. Retail spaces may be transformed into dynamic, captivating settings that emotionally connect with customers through the use of this comprehensive strategy.

Strategies for constructing harmonious colour combinations by art students with autism spectrum disorders

Introduction. The survey discussed in the article represents the first experience of an empirical study of the peculiarities characterising the ways of construction and perception of colour harmony by students with autism spectrum disorders – professional art education learners. The relevance of the study is conditioned by new trends in education related to the need to create an inclusive and favourable environment for people with autism. This environment is necessary for their successful integration and professional training in art specialities that are considered a promising area for professional realisation of people with autism. Methods. The survey was carried out using the experimental method involving 21 participants with autism spectrum disorders (mean age = 20.4 years; SD = 2.4; 9 males, 12 females). The participants’ answers in the experimental group were compared with those of an age-, gender-, and education-matched control group (N=21). The participants’ task was to match two given shades with a third one in the palette, for the colour combination to be as harmonious as possible. The experimental palette allowed to change the hue, lightness and chroma of shades. Results. The participants with autism spectrum disorders were twice as likely to choose yellow (23.8% compared to 12.4% in the control group) and purple shades (16.2% compared to 9.5%); hardly used orange (1.9%) and blue (4.8%) and preferred lighter shades (the mean L value was 67.8 compared to the control group’s 63.0). The chroma of the selected shades correlated with their hue and lightness. The stimulus selection strategy depended on the distance (∆E*00) between the given (upper and lower) shades in the CIELAB colour space and was based on a specific “geometry” (a particular ratio of values characterising the angles and side lengths formed by the given and selected shades, as well as a preference for a particular triangle area and its type). Discussion. The experiment showed that the students with autism spectrum disorders differed markedly from neurotypical students in a number of indicators when constructing a colour harmony. The experimental group participants’ responses showed a “preference for sameness” characteristic of autism. The significant inter-group differences were applied more to the lightness and chroma of the chosen shades than to their hue. The shades preferred by the participants with autism spectrum disorders better matched the conditions of the habitual “chromatic diet” and the colour’s statistics in nature. The observed specificity may also reflect the reduced ability to generalise and average out colours in terms of holistic perception, specific to autism. Conclusion. The survey results make an important contribution to the improvement of the professional training methodology for art students, and for the development of scientifically based educational approaches to teaching people with autism spectrum disorders, primarily in the context of the formation of colour-related competencies; in addition, they may provide new impulses for investigating the fundamental mechanisms of cognitive processing of colour-related information.

RÉSUMÉ AND PORTFOLIO DESIGN IN DESIGNER PORTFOLIO COURSE RÉSUMÉ EVALUATIONS

A résumé is a way for the designer to express his or her skills and experience. A creative résumé highlights the designer's unique talents and personal style. When recruiters evaluate candidates based on their résumés, a creative résumé stands out and can strike a favorable first impression. This is an opportunity to highlight the designer's creativity and design skills. Harmonious color palettes, layouts and graphic elements demonstrate the designer's communication skills. It is essential for designers to design their résumé in an informative, easy-to-read and eye-catching way, as this document is not only a job application form but also a design product. This article aims to discuss why a designer's résumé should be creative and analyzes the résumés created by students in the Portfolio Design course conducted by the researcher. In addition, the importance of the Portfolio Design course, a course in which design students learn to use their résumés to identify their career goals and highlight their experiences and skills, is emphasized.

Musical Color Harmony: Application of the Principles of Musical Harmony to Produce Color Hue Sets

Abstract Aesthetic response to the visual harmony of color combinations is a very personal and widely differing subjective experience. To the contrary, musical harmony - consonance and dissonance - are mathematically defined and certain combinations of notes exhibit near universal aesthetic agreement across the globe. Although numerous metaphysicians, philosophers, scientists, poets, artists, and musicians have speculated on the existence of a relationship between color and music for over 2000 years, the establishment of a correlation between color and musical harmony has been elusive. The author describes a framework, Musical Color Hue Harmony (MCHH), initially developed for video display systems, that correlates musical and color harmonic consonance and dissonance by applying the physics of aural harmonic resonance and theories of musical harmony to produce sets of “harmonious” color hues based on the mathematically defined frequency relationships between two or more musical pitches. The methodology is applicable to any musical tuning system and any color hue wheel configuration. Color attributes of brightness/luminance and saturation/chroma are presently beyond the scope of the framework.

The Color Harmony Estimation Model Construction Based on Two Layers of MLE and BPNN in the Color Matching Field

In the field of art, color matching is widely used in various art designs, such as images, posters, clothing, and interior home design. Among them, harmonious color matching is the decisive factor in whether a design is popular or not. To solve the problem of estimating color harmony, this study analyzes from the perspective of color pairs and uses the two-layer maximum likelihood estimation method to make preliminary predictions of color harmony by statistically modeling paired color preferences in existing datasets. After obtaining the preliminary estimation of color harmony, multiple linear regression is selected for denoising processing. Subsequently, the preliminary prediction results were refined using a backpropagation neural network, extracting various color features in different color spaces, and ultimately obtaining accurate harmony estimates. The results indicate that, compared with existing methods, the proposed method can simulate the aesthetic cognition of different users towards different color themes. Under the same statistical method, the model can maintain good harmony estimation and experimental results. This method can promote the development of related research fields, such as quickly evaluating the color harmony of an image, and one click color changing in scenes such as clothing, home, 3D models, etc. according to different user needs.

Exploring and Practicing the Quantification of Interior Design Colors from an IKEA Design Perspective

With the improvement of life quality, color plays an increasingly important role in interior design. This article, guided by IKEA's design philosophy, deeply explores the scientific method of interior design color quantification, aiming to enhance the aesthetics and functionality of the living environment through precise color matching. The method leverages the dkimageapp module to achieve scientific quantification and analysis of colors, thereby accomplishing efficient color pairing. In terms of methodology, this article elaborates on the importance and application of color palette, color difference, and color wheel calculations. Color palette calculation assists designers in grasping the distribution and harmony of colors; color difference calculation utilizes the CIEDE2000 formula to provide an accurate assessment of color differences; color wheel calculation serves as a visual tool for understanding color relationships. Empirical research has verified the effectiveness and practicality of the algorithms, ensuring the reliability of the study. This article ultimately summarizes the research findings and looks forward to their widespread application in the field of interior design, contributing to the creation of a better living environment, while stimulating further exploration and innovation to promote the continuous development of the interior design industry

FLORA MOSAIC MOTIF ON CASUAL DRESS USING ITAJIME AND ECOPRINT TECHNIQUES

Flora Mozaik displays the beauty of flowers with six symmetrical petals reinforced by fern leaves, the diversity of round paper mosaics in green color harmony that represents the growth and harmony of nature. The research aims to analyze the market response to fashion products developed through itajime and ecoprint techniques using natural dyes. The research method used in this study is the R&D method with the PPE (Planning, Production, and Evaluation) model to explore floral mosaic motifs on casual dresses using itajime and ecoprint techniques. This R&D research method details the steps in each stage of fashion product development from initial planning to evaluation. The results of the public test showed a positive response from the age group of 19-26 years, towards the fashion products produced through itajime and ecoprint techniques with natural dyes as indicated by the high level of preference (really like and like) of the respondents. This shows that continuous innovation in production technology makes it possible to produce products that are in demand in the market, and the results of the public testing confirmed strong acceptance among the subjects.

Analysis and Study of Color Design in Graphic Design

Color selection and application in graphic design are crucial as colors provide impactful visual impressions that enhance the meaning of the final graphic design works. Therefore, designers need to exercise careful control over color choices to achieve harmonious color combinations that convey essential graphic design messages effectively.

On harmonious coloring of hypergraphs

A harmonious coloring of a $k$-uniform hypergraph $H$ is a vertex coloring such that no two vertices in the same edge have the same color, and each $k$-element subset of colors appears on at most one edge. The harmonious number $h(H)$ is the least number of colors needed for such a coloring. The paper contains a new proof of the upper bound $h(H)=O(\sqrt[k]{k!m})$ on the harmonious number of hypergraphs of maximum degree $\Delta$ with $m$ edges. We use the local cut lemma of A. Bernshteyn.

Modified Roll Envelope Technique Combined With Apically Repositioned Flap (MRARF) for Peri-Implant Soft Tissue Augmentation-A Case Series.

In the present case series, we performed implant surgery using a modified roll envelope technique and an apically repositioned flap (MRARF). To improve patients' peri-implant soft tissue phenotypes, they underwent dental implantation following the buccal contour concavities, inadequate keratinized tissue width, and soft tissue thickness simultaneously. This case series includes 4 patients treated between July 2021 and February 2022 who received dental implants and guided bone regeneration treatment 6 months earlier and were to be taken up for second-stage surgery. They were eligible for the MRARF technique if each implant site showed a labial and buccal deficiency and a reduced keratinized mucosa width than the adjacent teeth. Sutures were removed 2 weeks after surgery, and a provisional restoration was delivered. A final impression was taken at 6 weeks to produce the definitive implant-supported restoration. All surgery sites healed uneventfully, and no postoperative pain or excessive swelling was reported. The modified flap design allowed for increasing the width and thickness of keratinized mucosa with a minimally invasive technique. A harmonious color, texture, and mucogingival junction position that matched the surrounding tissue and adjacent teeth was achieved, and all patients were satisfied with the final results. MRARF at second-stage implant surgery could obtain satisfactory results regarding vertical and horizontal aesthetic gingival contours and an adequate width and thickness of keratinized mucosa around the implants.

Image-Driven Harmonious Color Palette Generation for Diverse Information Visualization.

Color has been widely used to encode data in all types of visualizations. Effective color palettes contain discriminable and harmonious colors, which allow information from visualizations to be accurately and aesthetically conveyed. However, predefined color palettes not only lack the flexibility of custom color palette generation but also ignore the context in which the visualizations are used. Designing an effective color palette is a time-consuming and challenging process for users, even experts. In this work, we propose the generation of an image-based visualization color palette to exploit the human perception of visually appealing images while considering visualization cognition. By analyzing color palette constraints, including harmony, discrimination, and context, we propose an image-driven color generation method. We design a color clustering method in the saliency-hue plane based on visual importance detection and then select the palette based on the visualization color constraints. In addition, we design two color optimization and assignment strategies for visualizations of different data types. Evaluations through numeric indicators and user experiments demonstrate that the palettes predicted by our method are visually related to the original images and are aesthetically pleasing, supporting diverse visualization contexts and data types in practical applications.

Prussian blue pigment: Bridging the historical palette to modern innovations

This comprehensive review explores the multifaceted realm of Prussian Blue, a pigment with a rich history and varied applications tracing its origins, artistic applications, and chemical properties. Beginning with its origins as a laboratory creation, the paper traces its evolution into a revered pigment in the artistic world. The review explores the electronic transitions responsible for Prussian Blue's deep blue hue, shedding light on the intricate chemistry behind its vivid coloration. Additionally, the pivotal role of iron ions in determining the pigment's properties is examined in detail, highlighting the importance of precise composition in achieving desired color characteristics. Challenges in the reintegration of Prussian Blue into conservation and restoration projects are also explored, emphasizing the importance of careful preservation techniques to maintain the pigment's integrity and vibrancy. The review discusses the pigment's lightfastness and stability, addressing common issues such as fading and discoloration over time. A notable phenomenon of bronzing particularly associated with Chinese Blue has been characterized by the appearance of yellow or brown hues on the surface of the pigment, that has puzzled artists and conservators for centuries. The review delves into the underlying causes of bronzing, examining factors such as environmental conditions, pigment composition, and application techniques. The review explores the pigment's interactions with other blues and whites, offering insights into the spectrum of shades achievable through careful color mixing and layering techniques. The paper revisits the perennial debate surrounding the permanence of Prussian Blue. While some argue for its enduring stability and longevity, others point to instances of fading and discoloration observed in historical artworks. The manuscript navigates these conflicting perspectives, providing an understanding of Prussian Blue's permanence in different contexts. Prussian Blue stands as a testament to the symbiotic relationship between science and art, where its molecular structure and vibrant shades continue to inspire both chemists in laboratories and artists in studios. The Prussian Blue emerges as a captivating convergence of art and chemistry that has left an indelible mark on laboratory benches and artists' canvases. The unique interplay of ferric and ferrous ions, not only renders a deep blue color but also makes it sensitive to the variation of its environment. The interplay of its refractive index, bronzing tendencies, and tinting strength shapes its artistic applications, influencing the vibrant hues it contributes to diverse palettes. The permanence paradox surrounding Prussian Blue underscores the importance of precision in its preparation. As artists mix and blend, the pigment unveils its versatility, playing a pivotal role in color harmonies and shade variations. Beyond its role in art, Prussian Blue finds diverse applications in medicinal and industrial contexts. From its use as an antidote for heavy metal poisoning to its incorporation into high-performance materials such as batteries and sensors, Prussian Blue continues to demonstrate its versatility and utility in modern society. The review highlights these varied applications, showcasing Prussian Blue's enduring relevance and evolution beyond its historical roots.

The aesthetics of forming acting performance in children's theater performances

The theatrical performance embodies a multi-faceted aesthetic taste that has emerged from the creative human consciousness. As human thinking evolved and developed a love for play and entertainment, it began to fill its aspects with singing, acting, shaping, and decorating. The basics of this study consist of the primary form of theatrical performance and its symbols, meanings, and the use of children's theater in efforts to achieve visual and kinetic events through harmony and development of various means until it became the fundamental and essential role in using the actor's tools as a tangible sign and nucleus in the formation of the theatrical performance. This medium is especially true when the theatrical act gains a diverse aesthetic formation to entertain and delight children. Therefore, the researcher presented his study entitled "Aesthetics of Theatrical Performance Formation in Children's Theater (Jad and Yara in the World of Arts - Model)" in the light of four chapters according to the scientific research methodology, seeking to achieve the research goal of revealing the aesthetics of the formation of theatrical performance in the Jad and Yara in the World of Arts play. The study concluded with several results, the most important of which is that the aesthetics of theatrical performance were characterized by diversity, repetition, and change of visual forms, the use of kinetic performance of visual and auditory elements, and its intellectual and aesthetic significance. In addition, the consistent color harmony, in which the theatrical performance formed an interactive product, was a dynamic organization in which balance and form were transferred.

Auto-metric Graph Neural Network for Attack Detection on IoT-based Smart Environment and Secure Data Transmission using Advanced Wild Horse Standard Encryption Method

Smart cities (SCs) are being constructed with the huge placement of the Internet of Things (IoT). Real-time enhancements to life quality based on comfort and efficiency. The key concerns in most SCs that immediately impact network performance are security and privacy. Numerous approaches are proposed for secure data transmission, but the current methods do not provide high accuracy and it provide high computational time. To resolve these problems, an Auto-metric Graph Neural Network for Attack Detection and Secure Data Transmission using Optimized Enhanced Identity-Based Encryption in IoT (AGNN-AWHSE-ST-IoT) is proposed. Primarily, the input data is taken from the NSL-KDD dataset. The input data is gathered with the aid of NSL-KDD is pre-processed using three steps, crisp data conversion, splitting, and normalization. Then the Pre-processed input is fed into the Colour Harmony Algorithm (CHA) based feature selection to select the important features. After feature selection, the preferred features are given to the AGNN classifier. After classifying, the data is given to Enhanced Identity-Based Encryption (EIBE), and it is optimized using Wild Horse Optimizer (WHO) for transmitting the data more safely. The outcomes of the normal data are displayed using the LCD monitor. The AGNN-AWHSE-ST-IoT method is implemented in PYTHON. The AGNN-AWHSE-ST-IoT method attains 8.888%, 13.953%, 19.512% higher accuracy, 2.105%, 6.593%, 8.988% higher cumulative accuracy, 54.285%, 54.285%, 52.941% lower encryption time, 8.2%, 3.3%, 6.9% lower decryption time, 11.627%, 10.344%, 6.666% higher security level and 60.869%, 70% and 64% lower computational time than the existing approaches such as SBAS-ST-IoT, BDN-GWMNN-ST-IoT and DNN-LSTM-ST-IoT respectively.

Color Theme Evaluation through User Preference Modeling

Color composition (or color theme) is a key factor to determine how well a piece of art work or graphical design is perceived by humans. Despite a few color harmony models have been proposed, their results are often less satisfactory since they mostly neglect the variations of aesthetic cognition among individuals and treat the influence of all ratings equally as if they were all rated by the same anonymous user. To overcome this issue, in this paper we propose a new color theme evaluation model by combining a back propagation neural network and a kernel probabilistic model to infer both the color theme rating and the user aesthetic preference. Our experiment results show that our model can predict more accurate and personalized color theme ratings than state of the art methods. Our work is also the first-of-its-kind effort to quantitatively evaluate the correlation between user aesthetic preferences and color harmonies of five-color themes, and study such a relation for users with different aesthetic cognition.

Research on Emotional Analysis and Emotional Color Extraction Algorithm of Chinese Language and Literature Based on Emotional Computing

In China, the emotional response of diverse cultural bearers, including literature, movies, and other media, frequently mirrors the country's cultural improvement. Consequently, emotional analysis of the text and paintings may be used to examine the cultural evolution, determine its growth dynamics, and sort out its context. The project aims to investigate how well sophisticated affective computing performs in identifying and analyzing the emotional aspects of traditional Chinese literature and language. The study selects the Double Channel based Self-organized Residual Network-50 V2 (DC-SoResNet 50V2) algorithm based on a combination of deep learning algorithms and further improving the (DC-SoResNet 50V2) algorithm using Emperor penguin Colony optimizer (EPCO). Moreover, the color image and text features from traditional Chinese literature are extracted using hummingbird-based term frequency-inverse document frequency (HB-TF-IDF) and Stochastic Color Harmony Algorithm (SCHA). Comparisons are made between the proposed and standard approaches using the training and test sets, respectively. The training time of the proposed approach is stable at around 25.1 s, while the test time is steady at about 18.5 s. The emotion identification accuracy of the proposed method achieved average of 99.11 and 99.23% in testing and training sets for the entire datasets, respectively. Comprehensive analysis of classic literary works can be possible with the help of this research, which offers fresh viewpoints and theoretical references.

Automated Image-Based User Interface Color Theme Generation

Color plays an essential role in the design of user interfaces and significantly impacts the user experience. To create aesthetically pleasing and user-friendly interfaces, the colors of the user interface should be consistent with the images. The latter can be challenging to achieve, as images often have different colors and are often changed by editors or authors who do not have sufficient design knowledge. To solve this problem, we have developed a model that automatically determines the color theme of the user interface based on a given image. The model first extracts the most prominent colors from the image and then considers both aesthetic (color harmony and compatibility with the image) and usability aspects (color contrast, color diversity, and color strength). All color calculations are performed in the perceptually uniform color space CAM02-UCS. In addition, the model can be adapted to the user’s needs and requirements. To test the model, we implemented it in a web-based application in which the colors were automatically selected based on the featured image. The resulting color themes were then evaluated by the users, who were mainly professional designers. According to the results, the model generates color themes that are consistent with the image, aesthetic, and user-friendly. An important observation was also that color harmony can be achieved simply by using the most prominent colors of the image (regardless of their hue), suggesting that color harmony is strongly influenced by the context of use. The presented model holds significant practical importance as it can be utilized in various applications and tools. For instance, it can automatically choose a color theme for a user interface based on a particular image, such as a company logo or a product image. Moreover, it can dynamically adjust the colors of elements in real time based on the image that is visible simultaneously with the elements.

ChromaFusionNet (CFNet): Natural Fusion of Fine-Grained Color Editing

Digital image enhancement aims to deliver visually striking, pleasing images that align with human perception. While global techniques can elevate the image's overall aesthetics, fine-grained color enhancement can further boost visual appeal and expressiveness. However, colorists frequently face challenges in achieving accurate, localized color adjustments. Direct composition of these local edits can result in spatial color inconsistencies. Existing methods, including color style transfer and image harmonization, exhibit inconsistencies, especially at boundary regions. Addressing this, we present ChromaFusionNet (CFNet), a novel approach that views the color fusion problem through the lens of image color inpainting. Built on the Vision Transformer architecture, CFNet captures global context and delivers high-fidelity outputs, seamlessly blending colors while preserving boundary integrity. Empirical studies on ImageNet and COCO datasets demonstrate CFNet's superiority over existing methods in maintaining color harmony and color fidelity. Robustness evaluations and user studies have further validated the effectiveness of CFNet. In conclusion, CFNet introduces an innovative approach to seamless, fine-grained color fusion, paving the way for advancements in the domain of fine-grained color editing. Code and pretrained models are available at our project page: https://yidong.pro/projects/cfnet.

Self-attention-based generative adversarial network optimized with color harmony algorithm for brain tumor classification

ABSTRACT This paper proposes a novel approach, BTC-SAGAN-CHA-MRI, for the classification of brain tumors using a SAGAN optimized with a Color Harmony Algorithm. Brain cancer, with its high fatality rate worldwide, especially in the case of brain tumors, necessitates more accurate and efficient classification methods. While existing deep learning approaches for brain tumor classification have been suggested, they often lack precision and require substantial computational time.The proposed method begins by gathering input brain MR images from the BRATS dataset, followed by a pre-processing step using a Mean Curvature Flow-based approach to eliminate noise. The pre-processed images then undergo the Improved Non-Sub sampled Shearlet Transform (INSST) for extracting radiomic features. These features are fed into the SAGAN, which is optimized with a Color Harmony Algorithm to categorize the brain images into different tumor types, including Gliomas, Meningioma, and Pituitary tumors. This innovative approach shows promise in enhancing the precision and efficiency of brain tumor classification, holding potential for improved diagnostic outcomes in the field of medical imaging. The accuracy acquired for the brain tumor identification from the proposed method is 99.29%. The proposed BTC-SAGAN-CHA-MRI technique achieves 18.29%, 14.09% and 7.34% higher accuracy and 67.92%,54.04%, and 59.08% less Computation Time when analyzed to the existing models, like Brain tumor diagnosis utilizing deep learning convolutional neural network with transfer learning approach (BTC-KNN-SVM-MRI); M3BTCNet: multi model brain tumor categorization under metaheuristic deep neural network features optimization (BTC-CNN-DEMFOA-MRI), and efficient method depending upon hierarchical deep learning neural network classifier for brain tumour categorization (BTC-Hie DNN-MRI) respectively.