Premium
Optimization of color design for military camouflage in CIELAB color space
Author(s) -
Lin Chiuhsiang Joe,
Prasetyo Yogi Tri,
Siswanto Nio Dolly,
Jiang Bernard C.
Publication year - 2019
Publication title -
color research and application
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.393
H-Index - 62
eISSN - 1520-6378
pISSN - 0361-2317
DOI - 10.1002/col.22352
Subject(s) - camouflage , computer science , artificial intelligence , response surface methodology , field (mathematics) , computer vision , pattern recognition (psychology) , mathematics , machine learning , pure mathematics
The assessment of military camouflage is a key consideration in the modern military field. Traditionally, the assessment relies on traditional human visual detection tests because a large scale multi‐level and multi‐factor experiments are time‐ and resource‐consuming. One aspect of camouflage assessment, to which this current study pertains, entails improving upon or “enhancing” an existing or “selected” design. The current study presents a new and practical approach for enhancing the selected military camouflage by utilizing response surface methodology (RSM) of % L *, % a *, and % b * in CIELAB color space. Ten participants were recruited to evaluate 35 variations of % L *, % a *, and % b * on camouflage similarity index (CSI) and reaction time (RT). Based on RSM, the optimum combination occurs at L *: 61.4966, a *: −5.6505, and b *: 10.5114. In addition, a predictive algorithm to calculate the optimum shift of % L *, % a *, and % b * from the original camouflage to the improved camouflage derived from RSM is also proposed. The optimum shift occurs at −25% L *, −55% a *, and + 80% b *. In the end, a new design guideline is proposed for the enhancement of selected military camouflage, which adopts the present study's research findings.