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Embedded platform for local image descriptor based object detection

Author

Listed:
  • Kapela, Rafal
  • Gugala, Karol
  • Sniatala, Pawel
  • Swietlicka, Aleksandra
  • Kolanowski, Krzysztof

Abstract

The article presents novel idea of a hardware accelerated image processing algorithm for embedded systems. The system is based on the well known Fast Retina Keypoint (FREAK) local image description algorithm. The solution utilizes Field Programmable Gate Array (FPGA) as a flexible module that is used to implement hardware acceleration of a given part of the image processing algorithm. The approach presented in this paper is slightly different. Since we are using very fast FREAK descriptor it is not our purpose to implement full feature extraction algorithm in hardware but just its most time-consuming part which is brute force matcher based on the Hamming distance. Moreover our goal was to design very flexible system so that the feature detection and extraction algorithm can be replaced without any interruption in the hardware accelerated part.

Suggested Citation

  • Kapela, Rafal & Gugala, Karol & Sniatala, Pawel & Swietlicka, Aleksandra & Kolanowski, Krzysztof, 2015. "Embedded platform for local image descriptor based object detection," Applied Mathematics and Computation, Elsevier, vol. 267(C), pages 419-426.
    • Handle: RePEc:eee:apmaco:v:267:y:2015:i:c:p:419-426
    DOI: 10.1016/j.amc.2015.02.029
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    Cited by:

    1. Yan Lu & Kun Gao & Tinghua Zhang & Tingfa Xu, 2018. "A novel image registration approach via combining local features and geometric invariants," PLOS ONE, Public Library of Science, vol. 13(1), pages 1-18, January.

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