Abstract

CAINA, Darwin; CARILLO, René  and  CARRILLO, Marcelo. Técnicas de Visión Computacional para determinar el estado fitosanitario en plantaciones de brócoli. Siembra [online]. 2017, vol.4, n.1, pp.51-58. ISSN 2477-8850.  https://doi.org/10.29166/siembra.v4i1.499.

The demand for broccoli has increased significantly in the last years due to the benefits of its consumption for human health. This poses new challenges for producers, who increasingly rely on technology to improve production processes, increase yields and thereby meet the current demand. One of the technology fields that has gained interest in crop production the use of Computer Vision models, which can provide support and assistance in food production. This paper proposes an algorithm based on color detection of broccoli, which, at the macro level can identify phytosanitary problems in broccoli plantations; and, at the micro level can be used to identify the product that is suitable for consumption. The algorithm uses open source tools such as OpenCV and Python, so that it can be developed at low cost with results similar or better than those obtained with commercial softwares.

Keywords : computer vision; broccoli; digital image processing; OpenCV; HSV.

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