SciELO - Scientific Electronic Library Online

 
vol.64 issue3Traits of the sugar cane associated with tons of cane per hectare and sucrose (% cane)Detection of Eurhizococcus colombianus (Hemiptera: Margarodidae) in blackberry plants by near-infrared spectroscopy author indexsubject indexarticles search
Home Pagealphabetic serial listing  

Services on Demand

Journal

Article

Indicators

Related links

  • On index processCited by Google
  • Have no similar articlesSimilars in SciELO
  • On index processSimilars in Google

Share


Acta Agronómica

Print version ISSN 0120-2812

Abstract

CACERES FLOREZ, Camilo Andrés; AMAYA HURTADO, Darío  and  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

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

        · abstract in Spanish     · text in Spanish     · Spanish ( pdf )