@inbook{2adeb572532a44329e49329db43d2933,
title = "Towards Image Mosaicking with Aerial Images for Monitoring Rice Crops",
abstract = "Around 8 to 10 million Ton of rice are required in the following years to be able to supply the demand of the overall population. Analysis and monitoring of rice crops becomes nowadays very important issue for farmers, for ensuring a rice production level to cope this demand. This paper presents simulation results of an algorithm that allows to plan and create 2D maps using the technique of image mosaicking with multiple geo-referenced aerial images (multispectral images in the scope of the project). The planning algorithm is called Image Capture algorithm. It takes into account the area the UAV has to cover, the camera configuration, and the state of the UAV in order to define where to take the pictures to build the mosaic. The algorithm presented in this paper was developed in ROS (Indigo) and simulated in Gazebo. The results of this first approach to the 2D mapping of a rice crop allows to see that using the proposed algorithm, it is possible to automate the process of acquiring the pictures for creating the mosaic, ensuring that all the area of interest is covered. By using this algorithm, pictures will be acquired only in specific areas. Therefore, keeping the storage capacity on-board, under control.",
keywords = "Computer vision, Homography, Image mosaicking, Stitching, Unmanned Aerial Vehicles",
author = "Juan Rojas and Carol Martinez and Ivan Mondragon and Julian Colorado",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG 2017.",
year = "2017",
doi = "10.1007/978-3-319-54377-2\_24",
language = "English",
series = "Lecture Notes in Networks and Systems",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "279--296",
booktitle = "Lecture Notes in Networks and Systems",
address = "Germany",
}