Resumen

CACERES FLOREZ, Camilo Andrés; AMAYA HURTADO, Darío  y  RAMOS SANDOVAL, Olga Lucía. Methodology for pest damage recognition in Begonia semperflorens link & Otto (sugar flower) crop through image processing. Acta Agron. [online]. 2015, vol.64, n.3, pp.273-279. ISSN 0120-2812.  https://doi.org/10.15446/acag.v64n3.42657.

Nowadays, an important element in farming, is the use of technology, based on the analysis of the different factors that affect the succesfull development of the crops. The results are presented in the recognition of pests, in this work a computer machine vision, as a diagnostic was used. The images capturing were doing with a robotic air agent, equipped with a camera, capturing images of the state of a crop of a plant called ‘Flor de azúcar’ (Begonia semperflorens). These images are processed using machine vision techniques to identify the possible attack of pests on the crop. The techniques used are morphological filters, Gaussian blur filter and HSL. The main result of this work was accomplished, perform the detection of the perforation of the leaves as a result of pest attack, specifically slugs, snails, spider mites and leafminers

Palabras clave : Image processing; pest detection; farming monitoring; morphological filters; Gaussian Blur.

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