Work

Color Identification on Heterogeneous Bean Landrace Seeds Using Gaussian Mixture Models in CIE Lab* Color Space

Year: 2025

Type: article

Abstract: The classification of bean landraces based on their coloration is of particular interest, as the color of these plants is associated with the nutritional components present in their seeds. In this paper, the authors propose a procedure to identify the colors of heterogeneous color bean landraces based on the information from their digital images. The proposed methodology employs a three-dimensional histogram representation of the estimated color, expressed in the CIE L*a*b* color space, with an unsupervised learning method called the Gaussian Mixture Model. This approach facilitates the acquisition of representative information for the colors of a bean landrace, represented as points in the CIE L*a*b* color space. Furthermore, the K-nn method can be trained with these punctual representations to identify colors, yielding satisfactory results on landraces with homogeneous and heterogeneous seeds.

Source: Mathematical and Computational Applications

DOI: 10.3390/mca30030064

Authors: Adriana-Laura López-Lobato, Martha-Lorena Avendaño-Garrido, Héctor-Gabriel Acosta-Mesa, José-Luis Morales-Reyes, Elia-Nora Aquino-Bolaños

Institution: Universidad Veracruzana

Language: English

Topic: Smart Agriculture and AI

Subfield: Plant Science

Field: Agricultural and Biological Sciences

Domain: Life Sciences

SDG: Zero hunger

Open Access status: gold

Estimated APC paid: $1,689