Abstract
The paper presents an efficient method for real-time image analysis for manoeuvring of the underwater robot. Image analysis is done after computing the structural tensor components which unveil rich texture and texture-less areas. To allow a power efficient underwater operation in real-time the method is implemented on the Jetson TK1 self-standing graphics card using the CUDA compute architecture. The laboratory experimental results show that the system is capable of processing about 40 Full HD images per second while allowing orientation toward texture specific regions for obstacle avoidance.
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Acknowledgement
This work was done as a realisation of the research project financed by The Polish National Science Centre (NCN) and has the following project number UMO-2014/15/B/ST6/00609.
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Nawała, J., Cyganek, B. (2018). Real-Time Image Content Assessment for Underwater Robot Manoeuvring Based on Structural Tensor Analysis. In: Kurzynski, M., Wozniak, M., Burduk, R. (eds) Proceedings of the 10th International Conference on Computer Recognition Systems CORES 2017. CORES 2017. Advances in Intelligent Systems and Computing, vol 578. Springer, Cham. https://doi.org/10.1007/978-3-319-59162-9_48
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DOI: https://doi.org/10.1007/978-3-319-59162-9_48
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