Parallel Implementation of Souvola’s Binarization Approach on GPU
Department of CSE, College of Engineering Roorkee, Roorkee-247667,Uttarakhand, India
International Journal of Computer Applications 32(2):28-33, 2011
@article{singh2011implementation,
author={Brij Mohan Singh and Rahul Sharma and Ankush Mittal and Debashish Ghosh},
title={Article: Parallel Implementation of Souvola’s Binarization Approach on GPU},
journal={International Journal of Computer Applications},
year={2011},
volume={32},
number={2},
pages={28-33},
month={October},
note={Published by Foundation of Computer Science, New York, USA}
}
Binarization is widely used technique in many of the image processing applications. Fast algorithms are needed for fast and efficient image processing systems. Many algorithms of image processing and pattern recognition have recently been implemented on Graphic Processing Unit (GPU) for faster computational times. GPUs are most prominent hardware in utilizing parallelism and pipelining than general purpose CPUs. Moreover, Speed, programmability, and price become it more productive. In this paper, we proposed a parallel implementation of well known Sauvola’s local binarization algorithm for Optical Character Recognition systems. In this experiment, we achieved a computational speedup of parallel implementation on GPU 20.8x times faster than implementation on CPU. The speedup results of GPU are promising.
November 9, 2011 by hgpu
