Automated Sorting for Tomatoes using Artificial Neural Network
DOI:
https://doi.org/10.48112/jestt.v1i1.412Abstract
Abstract Views: 62
The experiment was conducted to test the sorting and grading of agricultural crops using image analysis technology. A locally factory-made studio cube shape with dimensions 50 * 75 * 75 and a camera with a sensor of the coupling device were used. The studio was equipped with triple lighting (red - green-blue), and photos were taken in the studio to study the external characteristics of the fruits of damage, quality and maturity using image processing technology and artificial neural network. The artificial neural network was used to predict damage the regression value was of 0.92062, quality the value of the regression was of 0.97981 and maturity of the regression was of 0.98654 by means of a regression scheme using the Levenberg-Marrquardt algorithm.
Keywords:
Tomatoes, Artificial Neural Network, Levenberg-Marrquardt algorithm
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