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Enhanced bio-inspired feature extraction for embedded application | IEEE Conference Publication | IEEE Xplore

Enhanced bio-inspired feature extraction for embedded application


Abstract:

In this paper, we propose an algorithm called Hessian ORB — Overlapped FREAK (HOOFR) to attack the feature matching problem in image processing. Our algorithm is based on...Show More

Abstract:

In this paper, we propose an algorithm called Hessian ORB — Overlapped FREAK (HOOFR) to attack the feature matching problem in image processing. Our algorithm is based on the combination of the ORB detector and the FREAK bio-inspired descriptor. We address some modifications related to the detection and the description processes in order to enhance HOOFR reliability, speed and memory fingerprint. The experiments on a widely used dataset demonstrate the considerable performance of HOOFR compared to SIFT, SURF or ORB in terms of the execution time and the matching quality for various matching contexts. Moreover, the performance is also tested by integrating HOOFR in object-tracking application on ODROID-XU4 platform, presenting a high potential of its implementation on embedded systems.
Date of Conference: 13-15 November 2016
Date Added to IEEE Xplore: 02 February 2017
ISBN Information:
Conference Location: Phuket, Thailand

References

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