Optimal thresholding for classification of bean plant growth
Abstract
Crop monitoring systems can serve to reduce costs, increase productivity and improve the quality of the harvest by creating the necessary environmental conditions for each stage. This paper presents a method for the classification of the growth phases of bean plants in their vegetative stage. A classification based on the area and dispersion of the pixels is proposed after an optimal RGB segmentation of the images of the bean plants in a controlled environment. To carry out this research, a database developed in 2019 at the Tecnológico Nacional de México campus Celaya was used after monitoring twenty bean plants from their germination stage to the first trifoliate leaf stage. The effectiveness of the proposal is verified by obtaining an adequate segmentation of the plants in the images that allows identifying the vegetative states with a smaller error than that reported in other works.
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