Innovative Machine Learning and Image Processing Methodology for Enhanced Detection of Aleurothrixus Floccosus

Valderrama Solis M.A.; Valenzuela Nina J.; Echaiz Espinoza G.A.; Yanyachi Aco Cardenas D.D.; Villanueva J.M.M.; Salazar A.O.; Villarreal E.R.L. · Electronics (Switzerland) (2025) · DOI: 10.3390/electronics14020358

Resumen

This paper presents a methodology for detecting the pest Aleurothrixus floccosus in citrus crops in Pedregal de Arequipa, Peru. The study employs simple random sampling during image collection to minimize bias, alternating and extracting leaves from different citrus trees. Image processing techniques, including noise reduction, edge smoothing, and segmentation, are applied for pest detection. Machine learning algorithms are used to classify the images, culminating in a robust detection methodology. A dataset of 1200 images was analyzed during the study.

Instituciones: Universidad Nacional de San Agustín de Arequipa