Munsell Soil Colour Classification Using Smartphones through a Neuro-Based Multiclass Solution
Metadata
Show full item recordEditorial
MDPI
Materia
Artificial neural networks Colour matching Munsell soil-colour chart Multiclassification
Date
2023-02-10Referencia bibliográfica
Pegalajar, M.C.; Ruiz, L.G.B.; Criado-Ramón, D. Munsell Soil Colour Classification Using Smartphones through a Neuro-Based Multiclass Solution. AgriEngineering 2023, 5, 355–368. [https://doi.org/10.3390/agriengineering5010023]
Abstract
Colour is a property widely used in many fields to extract information in several ways.
In soil science, colour provides information regarding the chemical and physical characteristics of
soil, such as genesis, composition, and fertility, amongst others. Thus, accurate estimation of soil
colour is essential for many disciplines. To achieve this, experts traditionally rely on comparing
Munsell colour charts with soil samples, which is a laborious process. In this study, we proposed
using artificial neural networks to catalogue soil colour with a two-step classification. Firstly, the hue
variable is estimated, and then the remaining two coordinates, value and chroma. Our experiments
were conducted using three different, common cameras (one digital camera and two mobile phones).
The results of our tests showed a 20% improvement in classification accuracy using the lowest-quality
camera and an average accuracy of over 90%.