A Greedy Algorithm for Highlighting of Color Dominance in Tomato Leaves and Fruit Segmentation

Abstract

The improvement of agricultural processesin recent years through the application of varioustechnologies, including computational algorithms, hasgiven rise to a field of research called precisionagriculture. This field aims to provide the plant withthe resources it needs for its development at the righttime. Deficiencies of a nutrient element necessary forthe development of a plant are mainly manifested in theleaves. In this paper, a greedy algorithm is proposedin order to optimize the segmentation method by colordominance that seeks to emphasize the dominanceof the green color present in the leaves and the redof the ripe fruits of tomato plants existing naturallyusing the RGB color model. The algorithm searchesa numerical range for the value that maximizes colordominance, the range is reduced until a stop conditionis reached. The objective function to maximize is theaverage performance when segmenting the pixels of theleaves and fruits. The classification images can beused in the detection of pests, diseases or nutritionaldeficiencies.