Parallelization of the local threshold and Boolean function based edge detection algorithm using CUDA
Raka Jovanović, Milan Tuba, Dana Simian · 2012
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.