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Image processing acceleration for intelligent unmanned aerial vehicle on mobile GPU

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Abstract

In this paper, we present an algorithm for providing visually-guided unmanned aerial vehicle (UAV) control using visual information that is processed on a mobile graphic processing unit (GPU). Most real-time machine vision applications for UAVs exploit low-resolution images because the shortage of computational resources comes from size, weight and power issue. This leads to the limitation that the data are insufficient to provide the UAV with intelligent behavior. However, GPUs have emerged as inexpensive parallel processors that are capable of providing high computational power in mobile environments. We present an approach for detecting and tracking lines that use a mobile GPU. Hough transform and clustering techniques were used for robust and fast tracking. We achieved accurate line detection and faster tracking performance using the mobile GPU as compared with an x86 i5 CPU. Moreover, the average results showed that the GPU provided approximately five times speedup as compared to an ARM quad-core Cortex-A15. We conducted a detailed analysis of the performance of proposed tracking and detection algorithm and obtained meaningful results that could be utilized in real flight.

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Acknowledgments

This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology. (Grant Number: 2012006817).

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Authors and Affiliations

  1. Department of Internet and Multimedia Engineering, Konkuk University, Seoul, Republic of Korea

    Dongwoon Jeon, Doo-Hyun Kim & Vladimir Tyan

  2. Department of Computer Engineering and Science, Konkuk University, Seoul, Republic of Korea

    Young-Guk Ha

Authors
  1. Dongwoon Jeon
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  2. Doo-Hyun Kim
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  3. Young-Guk Ha
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  4. Vladimir Tyan
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Corresponding author

Correspondence to Vladimir Tyan.

Additional information

Communicated by A. Jara, M.R. Ogiela, I. You and F.-Y. Leu.

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Jeon, D., Kim, DH., Ha, YG. et al. Image processing acceleration for intelligent unmanned aerial vehicle on mobile GPU. Soft Comput 20, 1713–1720 (2016). https://doi.org/10.1007/s00500-015-1656-y

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