A Method for the Detection and Reconstruction of Foliar Damage caused by Predatory Insects

Management of agricultural production and rural activities has been supported by recognizing machine learning patterns and algorithms, as in the automation of leaf analysis. However, leaf border damage compromises leaf structures, making it difficult to estimate the lost contours. Effects caused by...

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Bibliographic Details
Published in2021 IEEE 45th Annual Computers, Software, and Applications Conference (COMPSAC) pp. 1502 - 1507
Main Authors Silva Vieira, Gabriel Da, Maria de Sousa, Naiane, Rocha, Bruno, Fonseca, Afonso U., Soares, Fabrizzio
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.07.2021
Subjects
Crops
Image reconstruction
Image restoration
inpainting
insect predation
Insects
precision agriculture
smart farming
Software
Training
Visualization
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Summary:Management of agricultural production and rural activities has been supported by recognizing machine learning patterns and algorithms, as in the automation of leaf analysis. However, leaf border damage compromises leaf structures, making it difficult to estimate the lost contours. Effects caused by predatory insects are difficult to be monitored by inspection processes, and the harmful results caused by them can deteriorate the performance of machine learning models. In this sense, plant leaves that are not fresh or intact are avoided. Consequently, the number of samples for use in training steps is reduced, leading to problems of data balancing and limited generalization models. This study presents an automatic method for reconstructing an injured leaf at a probable stage before defoliation. Thus, the reconstruction of damaged leaves can be used to maximize the number of samples in the plant species classification processes and provide visible results for the agronomic analysis of regions of occurrence of leaf damage and the components of the primary leaf structure affected by predatory insects. Based on the experimental results, we conclude that the proposed approach can accurately delimit the injured leaf silhouette and restore the leaf regions affected by herbivory attacks.
DOI:10.1109/COMPSAC51774.2021.00223