Abstract
This chapter presents a methodology for the generation of paths from surveillance ground maps. The methodology detects and monitors texture patterns across consecutive images using an online sequential algorithm that creates piecewise linear approximation of the monitored trajectory. It takes under consideration the local structure of the patterns in order to extract a local path. The overall global path is sequentially formed from each segment. We present the preprocessing steps used to extract patterns of interest from an image and the results from two case study examples. The methodology has applications in the autonomous path planning of aerial vehicles following a specified structure, such as that of a river or road.
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The authors thanks some programming contributions made by former students for implementing some parts of this project sponsored by CART Center.
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Michalopoulos, K., Bebis, G., Bourbakis, N. (2022). Synthesizing 2D Ground Images for Maps Creation and Detecting Texture Patterns. In: Virvou, M., Tsihrintzis, G.A., Tsoukalas, L.H., Jain, L.C. (eds) Advances in Artificial Intelligence-based Technologies. Learning and Analytics in Intelligent Systems, vol 22. Springer, Cham. https://doi.org/10.1007/978-3-030-80571-5_2
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