Defining the perceptual threshold for hair volume: A method for aligning image‐based quantification with sensory evaluation

Abstract Objective Instrumental methods for measuring hair volume can detect physical differences that are not perceptible to consumers, creating a disconnect between in‐vitro measurements and real‐world perception. This study aimed to establish the Just‐Noticeable Difference (JND) for hair volume and to develop a predictive model incorporating hair waviness to better align instrumental data with sensory evaluation. Methods Bulk volume and waviness were quantified from hair swatches using a custom image‐analysis framework. Volume was determined via pixel intensity‐based fibre density classification, while waviness was derived from an amplitude–frequency analysis of the detrended medial axis. Sensory evaluation was conducted by an expert panel across controlled four‐swatch sets with defined volume differences (ΔV ≈ 5, 3 and 2 cm 2 ). Mean sensory rank was used as the primary perceptual metric. A multivariable Ordinary Least Squares regression model was developed and validated using Leave‐One‐Group‐Out Cross‐Validation across 35 independent sets. Results A perceptual threshold of ΔV ≈ 3 cm 2 was identified as the JND for hair volume. At ΔV ≈ 5 cm 2 , instrumental and sensory rankings were in strong agreement, whereas at ΔV ≈ 2 cm 2 , perceptual discrimination failed. Regression analysis confirmed bulk volume as the dominant predictor of perceived volume (β = 0.798, p < 0.001), with waviness providing a significant secondary contribution (β = 0.135, p = 0.005; Adjusted R 2 = 0.660). A waviness correction factor ( k ≈ 0.169) was derived, and cross‐validation demonstrated robust predictive performance (66.67% top‐rank accuracy; 94.87% top‐two accuracy). Conclusion This study establishes the quantitative perceptual threshold for hair volume and introduces a morphology‐aware correction model that aligns instrumental measurements with human perception. Together, these tools provide a practical framework for ensuring that volumising product claims are both physically measurable and perceptually meaningful.

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Journal
International Journal of Cosmetic Science
Published
2026-06-09
DOI
https://doi.org/10.1111/ics.70117
Primary Topic
Hair Growth and Disorders
Type
article
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article

Defining the perceptual threshold for hair volume: A method for aligning image‐based quantification with sensory evaluation

N. Muthunilavan, R. Sridhar Rajam, G. Gurulakshmi
International Journal of Cosmetic Science
Hair Growth and Disorders
article

Defining the perceptual threshold for hair volume: A method for aligning image‐based quantification with sensory evaluation

N. Muthunilavan, R. Sridhar Rajam, G. Gurulakshmi
article en

Abstract

Abstract Objective Instrumental methods for measuring hair volume can detect physical differences that are not perceptible to consumers, creating a disconnect between in‐vitro measurements and real‐world perception. This study aimed to establish the Just‐Noticeable Difference (JND) for hair volume and to develop a predictive model incorporating hair waviness to better align instrumental data with sensory evaluation. Methods Bulk volume and waviness were quantified from hair swatches using a custom image‐analysis framework. Volume was determined via pixel intensity‐based fibre density classification, while waviness was derived from an amplitude–frequency analysis of the detrended medial axis. Sensory evaluation was conducted by an expert panel across controlled four‐swatch sets with defined volume differences (ΔV ≈ 5, 3 and 2 cm 2 ). Mean sensory rank was used as the primary perceptual metric. A multivariable Ordinary Least Squares regression model was developed and validated using Leave‐One‐Group‐Out Cross‐Validation across 35 independent sets. Results A perceptual threshold of ΔV ≈ 3 cm 2 was identified as the JND for hair volume. At ΔV ≈ 5 cm 2 , instrumental and sensory rankings were in strong agreement, whereas at ΔV ≈ 2 cm 2 , perceptual discrimination failed. Regression analysis confirmed bulk volume as the dominant predictor of perceived volume (β = 0.798, p < 0.001), with waviness providing a significant secondary contribution (β = 0.135, p = 0.005; Adjusted R 2 = 0.660). A waviness correction factor ( k ≈ 0.169) was derived, and cross‐validation demonstrated robust predictive performance (66.67% top‐rank accuracy; 94.87% top‐two accuracy). Conclusion This study establishes the quantitative perceptual threshold for hair volume and introduces a morphology‐aware correction model that aligns instrumental measurements with human perception. Together, these tools provide a practical framework for ensuring that volumising product claims are both physically measurable and perceptually meaningful.

International Journal of Cosmetic Science
Çevre, Şehircilik ve İklim Değişikliği Bakanlığı (TR)
Reduced inequalities
Openalex Percentile: Top 6%
Hair Growth and Disorders
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Defining the perceptual threshold for hair volume: A method for aligning image‐based quantification with sensory evaluation — N. Muthunilavan, R. Sridhar Rajam, et al. · International Journal of Cosmetic Science (2026) | TGRS Research Map | TGRS