Resumen

MOREANO, Gabriel; CAJAMARCA, Julio  y  TENICOTA, Alex. Precision Agriculture: Preprocessing and Segmentation of Images to Obtain an Autonomous Land Navigation Route. Rev Politéc. (Quito) [online]. 2019, vol.44, n.2, pp.43-50. ISSN 2477-8990.  https://doi.org/10.33333/rp.vol44n2.05.

Precision agriculture seeks to increase the productivity of agricultural activities worldwide, autonomous navigation is a fundamental objective in this development framework because most agricultural activities involve extensive displacement of people or vehicles; Autonomous land navigation on crop plots has certain complications such as the sliding of vehicles on the land, which complicates the implementation of odometry systems, another complication is the difficulty of implementing navigation marks to use location systems. This work presents a computer vision system that intends to use the crop rows as a navigation mark for an agricultural vehicle emulating the behavior of a line follower robot. A camera takes 30 frames per second that will be processed by an algorithm that will eliminate problems of perspective, ambient light and obstacles in the crop to efficiently identify the crop row that is just below the vehicle. With the navigation mark and making an approximation of the longitudinal dimensions of reality with the longitudinal dimensions in pixels of the images, an estimated state of the vehicle can be obtained with respect to the previously identified mark.

Palabras clave : computer vision; segmentation; OpenCV; precision agriculture; C++.

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