RT Journal Article
T1 Color-based discrimination of color hues in rock paintings through Gaussian mixture models: a case study from Chomache site (Chile)
A1 Sepúlveda, Marcela
A1 Cabello, Gloria
A1 Bastías, Fernando
A1 Cerrillo Cuenca, Enrique
AB The article explores advanced image processing techniques for pigment discrimination in rock art paintings, emphasizing color separation using RGB (red, green, blue) and LHCUv (Luminance, Hue, Chroma) imagery. It highlights the use of dimensionality reduction methods such as Principal Components Analisys PCA and Independent Component Analysis (ICA), with a focus on Gaussian Mixture Models (GMM) for probabilistic classification of image elements. This approach, applied to the Chomache archaeological site on the northernmost coast of the Atacama Desert in Chile, reveals previously undetected motifs and details, offering a nuanced perspective in rock art documentation and analysis. This proposal reinforces the value of rock art panel not only as a finished product but as a process.
PB Springer
YR 2024
FD 2024-05-27
LK https://hdl.handle.net/20.500.14352/104786
UL https://hdl.handle.net/20.500.14352/104786
LA eng
NO Cerrillo-Cuenca, E., Sepúlveda, M., Cabello, G. et al. Color-based discrimination of color hues in rock paintings through Gaussian mixture models: a case study from Chomache site (Chile). Herit Sci 12, 169 (2024). https://doi.org/10.1186/s40494-024-01239-9
DS Docta Complutense
RD 12 abr 2025