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Aggregate and Category-Level Skin Fidelity Across LED Sources: Evaluating TM-30 Skin Samples with an Expanded Skin-Reflectance Library

Submitted:

09 July 2026

Posted:

14 July 2026

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Abstract
ANSI/IES TM-30-24 designates CES #15 and CES #18 as skin-representative color-evaluation samples, summarized by their mean individual fidelity (Rf,CES15,18). This analysis tested how well that two-sample mean represents average fidelity and category-level variation across a 100-spectrum skin-reflectance library stratified into five lightness-defined categories, evaluated across 1,432 architectural LED sources from the DTU PhotoLED database. Rf,CES15,18 closely tracked mean fidelity across the full reference library (r = 0.9976; RMSE = 0.84 Rf points). Benchmarked against all 4,950 possible two-spectrum means from the same library, it exceeded 85.7% of pairs in correlation and 82.7% in RMSE, favorable performance that was not unique. Raw category means within individual sources differed by 4.74 Rf points on average and by as much as 10.66 points. This ordering tracked chroma and was largely captured by the lightness-chroma geometry of the sampled spectra; little category-specific structure remained once that geometry was modeled, and the ordering was not fixed across the two reflectance libraries. Compact subsets were tested under source-only holdout and under simultaneous source-and-skin-spectrum holdout. Greedy selection held a modest source-held-out error advantage over an optimized category-matched random search at 9 to 10 samples. Under simultaneous holdout, subsets of that size preserved source-rank recovery, while reconstruction of unseen category means carried median errors near 1 Rf point. CES #15/#18 therefore serves as a favorable aggregate indicator within this library. Characterizing variation across the sampled skin-reflectance locus requires broader reflectance sets.
Keywords: 
;  ;  ;  ;  
Subject: 
Engineering  -   Other
Copyright: This open access article is published under a Creative Commons CC BY 4.0 license, which permit the free download, distribution, and reuse, provided that the author and preprint are cited in any reuse.
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