About

Renzo Shamey is a distinguished professor in the Wilson College of Textiles at NC State University, specializing in colour science and technology, dyeing, and finishing processes. He obtained his Bachelor of Engineering in 1989 through a five-year program that combined engineering and chemistry courses, and gained practical experience working in textile mills in dyeing and finishing industries for three years in various roles including process engineer and section manager. He further pursued a Master of Science degree in Dyeing and Finishing at Leeds University, graduating with distinction in 1993, and continued his doctoral studies there from 1993 to 1997, focusing on modelling and real-time control of dye concentration in package dyeing processes. His postdoctoral research at Leeds was sponsored by Unilever, and he later joined Heriot-Watt University in Scotland as a Lecturer in Dyeing, Printing, and Finishing, receiving a commendation for excellence in teaching in 2002. Since 2003, he has been part of NC State University, where he served as Program Director for undergraduate and graduate programs in Polymer and Color Chemistry and Textile Chemistry. He has held leadership roles such as President of the Inter-Society Color Council and has been recognized as a Fellow of the Society of Dyers and Colourists, as well as a Chartered Colourist. His research interests encompass colour science, measurement and analysis of complex coloured patterns, computer applications in textile wet processing, dye application, and textile chemistry, with numerous PhD and Masters projects completed under his supervision. He is also an accomplished author and editor, contributing to books and the second edition of the 'Encyclopedia of Color Science and Technology.' His professional affiliations include societies such as the Society of Dyers and Colourists, the Optical Society of America, and the Society for Imaging Science and Technology. Renzo Shamey is committed to advancing knowledge in colour perception, dyeing processes, and textile chemistry, with ongoing research into AI systems for troubleshooting dyeing and printing problems, as well as developing novel techniques for dyeing polyolefins and studying fiber degradation.

Research topics

• Computer Science
• Artificial Intelligence
• Information Retrieval
• Optics
• Physics
• Psychology
• Library science
• Computer vision
• Data science
• Neuroscience
• Mathematics
• World Wide Web

Selected publications

• Effect of texture on suprathreshold color-difference tolerances. Part I. Dataset of visual tolerances

  Figshare · 2026-03-31

  otherOpen accessSenior author

  Surface texture is a critical factor influencing perceptual color-difference evaluations, with implications for both scientific research and industrial practice. This study examined how texture affects suprathreshold color-difference tolerances. A dataset was generated by simulating textured stimuli through a colorto-texture fusion model, which mapped 10 texture patterns onto 11 color centers, each sampled along 18 vector directions. The corresponding uniform samples were included as a reference group. Twenty-six observers assessed the stimuli on a color calibrated monitor using the method of adjustment, whereby test samples were adjusted until their perceived color difference matched ∗ units. Reliability of that of an anchor pair fixed at 2.1 ∆𝑬𝒂𝒃 the collected responses was assessed through examining intra- and inter-observer variability among visual responses. Statistical analysis confirmed that surface structure significantly impacted lightness, chroma, and hue tolerances. The most pronounced effects occurred for lightness, where specific textures produced significantly higher tolerances than the uniform baseline, with variations across color centers and texture patterns. Chroma and hue tolerances were also influenced, although the effects were generally less substantial. These findings demonstrate the critical role of surface texture in shaping visual tolerances and provide a robust dataset for advancing textile color-difference assessment.

  PublisherDOI

• Supplementary document for Effect of texture on suprathreshold color-difference tolerances. Part I. Dataset of visual tolerances - 7813772.pdf

  Figshare · 2026-03-31

  articleOpen accessSenior author

  fusion example

  PublisherDOI

• Perceived Lightness Differences in Complex Scenes

  Color Research & Application · 2026-04-03

  articleOpen accessSenior authorCorresponding

  ABSTRACT Psychophysical experiments were conducted to quantify perceived lightness differences between stimuli presented on three background types: a checkerboard pattern, a color‐averaged version of the checkerboard, and a uniform gray background. Color normal observers reported perceived differences between paired stimuli positioned either adjacent or separated by 3° or 8° visual angle. Significant effects of both background type and spatial separation were observed. The gray background produced noticeably smaller perceived lightness differences than either the checkerboard or color‐averaged backgrounds. Moreover, for the gray background, placing the stimuli at a larger distance substantially decreased perceived differences. This gap effect was less pronounced for the checkerboard or color‐averaged backgrounds, likely due to simultaneous contrast effects. The ability of several color difference models to predict the perceptual data was assessed using the Standardized Residual Sum of Squares (STRESS) index. All evaluated models yielded relatively high STRESS values (33.12–45.10, on a scale of 0–100), indicating limited agreement with observer judgments and underscoring the need for improved predictive models for complex visual scenes.

  PublisherDOI

• Effect of texture on suprathreshold color-difference tolerances: dataset of visual tolerances

  Journal of the Optical Society of America A · 2026-03-16

  articleSenior author

  Surface texture is a critical factor influencing perceptual color-difference evaluations, with implications for both scientific research and industrial practice. This study examined how texture affects suprathreshold color-difference tolerances. A dataset was generated by simulating textured stimuli through a color-to-texture fusion model, which mapped 10 texture patterns onto 11 color centers, each sampled along 18 vector directions. The corresponding uniform samples were included as a reference group. Twenty-six observers assessed the stimuli on a color-calibrated monitor using the method of adjustment, whereby test samples were adjusted until their perceived color difference matched that of an anchor pair fixed at 2.1Δ E a b ∗ units. Reliability of the collected responses was assessed through examining intra- and inter-observer variability among visual responses. Statistical analysis confirmed that surface structure significantly impacted lightness, chroma, and hue tolerances. The most pronounced effects occurred for lightness, where specific textures produced significantly higher tolerances than the uniform baseline, with variations across color centers and texture patterns. Chroma and hue tolerances were also influenced, although the effects were generally less substantial. These findings demonstrate the critical role of surface texture in shaping visual tolerances and provide a robust dataset for advancing textile color-difference assessment.

  PublisherDOI

• Supplementary document for Effect of texture on suprathreshold color-difference tolerances. Part I. Dataset of visual tolerances - 7813772.pdf

  Figshare · 2026-03-31

  articleOpen accessSenior author

  fusion example

  PublisherDOI

• Visual and instrumental assessment of moisture-induced color change in polyester fabrics

  AATCC Journal of Research · 2026-01-01

  articleOpen accessSenior authorCorresponding

  This study investigates the impact of varying moisture levels on the perceived color appearance of polyester fabrics through a controlled psychophysical experiment involving human observers and instrumental colorimetric assessments. A total of 27 fabric samples across 9 color families and 3 depths of shade were evaluated under 3 moisture conditions: dry, 20% wet, and 120% wet. Observers performed paired comparisons using the AATCC Gray Scale for Color Change and categorical judgments of lightness, brightness (chroma), and hue shift. A total of 9720 assessments were thus obtained. Intra- and inter-observer consistency was assessed using STRESS indices and Cohen’s or Fleiss’ Kappa coefficients. Results showed that lightness was the most reliably judged perceptual attribute, with high consistency across and within observers, while brightness and hue judgments were more variable. Exploratory analysis revealed that higher moisture contrasts led to stronger perceived color differences, with directional hue shifts typically occurring along the red–blue directions. One-way ANOVA and Tukey HSD tests confirmed statistically significant differences between all moisture level comparisons. Instrumental color differences (ΔE 0 0 , ΔL, ΔC, ΔH) exhibited moderate correlation with observer ratings ( r = 0.5812), with the highest agreement observed for lightness (70.21%), followed by brightness (38.72%) and hue shift (27.98%). These findings highlight the limitations of relying solely on instrumental data when evaluating color under variable moisture conditions.

  PublisherDOI

• Effect of texture on suprathreshold color-difference tolerances. Part I. Dataset of visual tolerances

  Figshare · 2026-03-31

  otherOpen accessSenior author

  Surface texture is a critical factor influencing perceptual color-difference evaluations, with implications for both scientific research and industrial practice. This study examined how texture affects suprathreshold color-difference tolerances. A dataset was generated by simulating textured stimuli through a colorto-texture fusion model, which mapped 10 texture patterns onto 11 color centers, each sampled along 18 vector directions. The corresponding uniform samples were included as a reference group. Twenty-six observers assessed the stimuli on a color calibrated monitor using the method of adjustment, whereby test samples were adjusted until their perceived color difference matched ∗ units. Reliability of that of an anchor pair fixed at 2.1 ∆𝑬𝒂𝒃 the collected responses was assessed through examining intra- and inter-observer variability among visual responses. Statistical analysis confirmed that surface structure significantly impacted lightness, chroma, and hue tolerances. The most pronounced effects occurred for lightness, where specific textures produced significantly higher tolerances than the uniform baseline, with variations across color centers and texture patterns. Chroma and hue tolerances were also influenced, although the effects were generally less substantial. These findings demonstrate the critical role of surface texture in shaping visual tolerances and provide a robust dataset for advancing textile color-difference assessment.

  PublisherDOI

• Supplementary document for Effect of texture on suprathreshold color-difference tolerances. Part I. Dataset of visual tolerances - 7813772.pdf

  Figshare · 2026-03-31

  articleOpen accessSenior author

  fusion example

  PublisherDOI

• Diffusion of reactive dyes through cationized cellophane films

  Cellulose · 2025-10-13 · 1 citations

  articleOpen accessSenior author

  Abstract Cellophane films were cationized using 3–chloro–2–hydroxypropyltrimethyl ammonium chloride (CHPTAC) via a cold pad-batch method at four treatment levels (25, 50, 75, and 100 g/L). These modified films were used to investigate the diffusion behavior of five structurally diverse reactive dyes—C.I. Reactive (Blue 19, Violet 5, Red 198, Red 11, and Blue 109)—differing in molecular structure and sulfonate group content, under isothermal conditions at 60 °C. Time-lag diffusion plots were generated, and diffusion coefficients were calculated for all dyes and treatment levels.Cationization was found to significantly enhance dye diffusion through films compared to untreated samples. A typical increase of 2 × to 10 × in diffusion coefficient is observed due to CHPTAC treatment, depending on the dye structure and treatment level. Ionic interactions between the cationized cellulose and anionic dyes increased the driving force for diffusion. Diffusion coefficients generally decreased with the number of sulfonate groups, attributed to increased water solubility and steric hindrance.To better understand structure–property relationships, the equilibrium molecular geometries of the most stable conformers of selected dyes were calculated using density functional theory (DFT).Analysis of the optimized molecular geometries revealed a strong correlation between molecular coplanarity and dye mobility, and consequently, dye diffusion. Dyes with more coplanar geometries, such as C.I. Reactive Blue 109 and C.I. Reactive Violet 5, exhibited faster diffusion, likely due to reduced steric hindrance and more favorable molecular packing. In contrast, dyes with twisted or non-coplanar conformations, such as C.I. Reactive Red 198, displayed increased time-lags and lower diffusion rates, suggesting that geometric distortion can impede molecular transport properties.High resolution LC–MS analysis was also performed to characterize the structure and the ratio of vinyl sulfone versus sulfatoethylsulfone forms of C.I. Reactive Violet 5 and C.I. Reactive Blue 19 dyes, with approximately 47–53% de-esterification observed for these dyes. This provides additional insight into their diffusion behavior. These findings highlight the critical role of both substrate modification and molecular geometry in governing dye diffusion kinetics. This refined understanding can inform the design of more effective dyeing strategies for cationized cellulose in textiles and sustainable packaging applications.

  PublisherOA PDFDOI

• How Do I Look? The Impact of Unique and Intermediate Hues on Perceived Attractiveness

  Color Research & Application · 2025-04-22 · 1 citations

  articleOpen access1st authorCorresponding

  ABSTRACT Hering's unique hues (uHs) are hypothesized to exhibit enhanced perceptual salience due to their role in the opponent‐process theory of color vision, which posits that human color perception is structured around two opposing pairs: red–green and yellow–blue. This perceptual distinctiveness may influence aesthetic judgments, particularly in social contexts such as clothing attractiveness. Two experiments, involving 78 and 40 participants, respectively, assessed the influence of uHs and intermediate hues (iHs) on attractiveness ratings of computer‐generated models. These models were created by averaging photographs of real individuals and were presented against neutral gray backgrounds. Results demonstrated significantly higher attractiveness ratings for models dressed in uHs compared to iHs, with unique red (uR) showing particularly strong effects ( p < 0.0001, Cohen's d = 0.72–0.83). However, findings do not confirm superior perceptual salience of uHs relative to iHs. While the study provides valuable insights into the understanding of color perception in social contexts and its potential implications for clothing design, its findings are limited by the use of averaged uHs, a restricted sample of models, and controlled laboratory conditions, which may impact generalizability to diverse populations and real‐world settings.

  PublisherOA PDFDOI

Frequent coauthors

• Rolf G. Kuehni

  Color (United States)

  209 shared

• D. G. Hinks

  North Carolina State University

  19 shared

• Michael H. Brill

  Kingston Technology (United States)

  16 shared

• Eric Kirchner

  14 shared

• Juan Lin

  Fujian Agriculture and Forestry University

  13 shared

• Mark D. Fairchild

  11 shared

• Robert W. G. Hunt

  University of Leeds

  10 shared

• Michal Vik

  Technical University of Liberec

  9 shared

Labs

• Research Lab at Wilson College of TextilesPI

Education

• B.S., Engineering and Chemistry

  Not specified in the provided HTML

  1989

• M.S., Dyeing and Finishing

  Not specified in the provided HTML

Awards & honors

• Fellow of the Society of Dyers and Colourists (2010)
• Chartered Colourist (CCol) in the UK (2010)
• University Faculty Scholar at NCSU (2014)
• RS CIBA Distinguished Professor