Parallelization of the local threshold and Boolean function based edge detection algorithm using CUDA

Authors:
Raka Jovanovic;Milan Tuba;Dana Simian
Affiliations:
University of Belgrade, Institute of Physycs, Belgrade, Serbia;Megatrend University Belgrade, Faculty of Computer Science, Belgrade, Serbia;Lucian Blaga University of Sibiu, Department of Computer Science, Sibiu, Romania
Venue:
BICA'12 Proceedings of the 5th WSEAS congress on Applied Computing conference, and Proceedings of the 1st international conference on Biologically Inspired Computation
Year:
2012

Citing 3
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Local threshold and Boolean function based edge detection

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Abstract

In this paper we present a parallelized algorithm for edge detection for gray scale images. The chosen method is the local threshold and boolean function based edge detection. This method differs from common edge detectors in the use of bit map patterns instead of analyzing gradient changes in the image for edge recognition. The parallelization is implemented on the GPU, exploiting its multithreaded, many-core processor power using NVIDIA's CUDA (Compute Unified Device Architecture). We show in our tests the significant speedup of parallelized algorithm compared to the sequential one.