Munsell Soil Colour Classification Using Smartphones through a Neuro-Based Multiclass Solution
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 e...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-02-01
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| Series: | AgriEngineering |
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| Online Access: | https://www.mdpi.com/2624-7402/5/1/23 |
| _version_ | 1797614077775708160 |
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| author | M. C. Pegalajar L. G. B. Ruiz D. Criado-Ramón |
| author_facet | M. C. Pegalajar L. G. B. Ruiz D. Criado-Ramón |
| author_sort | M. C. Pegalajar |
| collection | DOAJ |
| description | 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%. |
| first_indexed | 2024-03-11T07:03:34Z |
| format | Article |
| id | doaj.art-7b886cebb2e8413eafea878dbb78cf35 |
| institution | Directory Open Access Journal |
| issn | 2624-7402 |
| language | English |
| last_indexed | 2024-03-11T07:03:34Z |
| publishDate | 2023-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | AgriEngineering |
| spelling | doaj.art-7b886cebb2e8413eafea878dbb78cf352023-11-17T09:03:13ZengMDPI AGAgriEngineering2624-74022023-02-015135536810.3390/agriengineering5010023Munsell Soil Colour Classification Using Smartphones through a Neuro-Based Multiclass SolutionM. C. Pegalajar0L. G. B. Ruiz1D. Criado-Ramón2Department of Computer Science and Artificial Intelligence, University of Granada, 18014 Granada, SpainDepartment of Software Engineering, University of Granada, 18014 Granada, SpainDepartment of Computer Science and Artificial Intelligence, University of Granada, 18014 Granada, SpainColour 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%.https://www.mdpi.com/2624-7402/5/1/23artificial neural networkscolour matchingMunsell soil-colour chartsmulticlassification |
| spellingShingle | M. C. Pegalajar L. G. B. Ruiz D. Criado-Ramón Munsell Soil Colour Classification Using Smartphones through a Neuro-Based Multiclass Solution AgriEngineering artificial neural networks colour matching Munsell soil-colour charts multiclassification |
| title | Munsell Soil Colour Classification Using Smartphones through a Neuro-Based Multiclass Solution |
| title_full | Munsell Soil Colour Classification Using Smartphones through a Neuro-Based Multiclass Solution |
| title_fullStr | Munsell Soil Colour Classification Using Smartphones through a Neuro-Based Multiclass Solution |
| title_full_unstemmed | Munsell Soil Colour Classification Using Smartphones through a Neuro-Based Multiclass Solution |
| title_short | Munsell Soil Colour Classification Using Smartphones through a Neuro-Based Multiclass Solution |
| title_sort | munsell soil colour classification using smartphones through a neuro based multiclass solution |
| topic | artificial neural networks colour matching Munsell soil-colour charts multiclassification |
| url | https://www.mdpi.com/2624-7402/5/1/23 |
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