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Cereal Crop Ear Counting in Field Conditions Using Zenithal RGB Images

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Developing a New Method of Transformation for Obtaining XYZ Color Values from RGB Images for Agricultural

Vahid Mohammadi¹, Keivan Ansari², Pierre Gouton¹

¹ImViA, UFR Sciences et Techniques, Université de Bourgogne, Franche-Comté, 21078 Dijon, France.

Sensors (Basel, Switzerland)

|December 17, 2024

Summary

This study developed a transformation matrix to convert digital image RGB color values to standard XYZ color coordinates for agricultural applications. The Macbeth color chart proved most effective, enabling accurate, low-cost plant color analysis.

Keywords:

Macbeth chart Munsell XYZ values color space transformation matrix

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Area of Science:

Agricultural Science
Color Science
Image Processing

Background:

Accurate color measurement is vital for plant monitoring and diagnostics in agriculture.
Standardized color values (e.g., XYZ) are needed for device-independent analysis.
Existing methods may be costly or inaccessible for widespread agricultural use.

Purpose of the Study:

To develop a transformation matrix for converting RGB values from digital images to XYZ color coordinates.
To create an accessible and cost-effective method for obtaining standard color information in agriculture.
To validate the technique using plant leaf samples.

Main Methods:

Calibration using Munsell and Macbeth color charts to derive transformation matrices.
Measurement of color coordinates for eight color charts.
Application of the transformation technique to leaf samples of six plant species.
Comparison of actual XYZ values with derived XYZ values from digital images.

Main Results:

The Macbeth color chart (24 colors) demonstrated superior performance.
Average ∆ELAB and CIEDE2000 values were below 1.77 and 1.97, respectively, indicating high accuracy.
The developed transformation matrix successfully converted RGB to XYZ values.

Conclusions:

The proposed transformation matrix provides a successful method for converting digital image RGB to XYZ color values.
This technique offers a quick, easy, and inexpensive solution for obtaining standard color information in agricultural applications.
The findings support the use of this method for plant monitoring and diagnostics.