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Parallel Implementation of Souvolaís Binarization Approach on GPU

by Brij Mohan Singh, Rahul Sharma, Ankush Mittal, Debashish Ghosh
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 32 - Number 2
Year of Publication: 2011
Authors: Brij Mohan Singh, Rahul Sharma, Ankush Mittal, Debashish Ghosh
10.5120/3878-5419

Brij Mohan Singh, Rahul Sharma, Ankush Mittal, Debashish Ghosh . Parallel Implementation of Souvolaís Binarization Approach on GPU. International Journal of Computer Applications. 32, 2 ( October 2011), 28-33. DOI=10.5120/3878-5419

@article{ 10.5120/3878-5419,
author = { Brij Mohan Singh, Rahul Sharma, Ankush Mittal, Debashish Ghosh },
title = { Parallel Implementation of Souvolaís Binarization Approach on GPU },
journal = { International Journal of Computer Applications },
issue_date = { October 2011 },
volume = { 32 },
number = { 2 },
month = { October },
year = { 2011 },
issn = { 0975-8887 },
pages = { 28-33 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume32/number2/3878-5419/ },
doi = { 10.5120/3878-5419 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:18:07.773682+05:30
%A Brij Mohan Singh
%A Rahul Sharma
%A Ankush Mittal
%A Debashish Ghosh
%T Parallel Implementation of Souvolaís Binarization Approach on GPU
%J International Journal of Computer Applications
%@ 0975-8887
%V 32
%N 2
%P 28-33
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
Abstract

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.

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Index Terms

Computer Science
Information Sciences

Keywords

Binarization CUDA GPU OCR Parallelization

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