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Towards Affordable Computing: SiftCU a Simple but Elegant GPU-based Implementation of SIFT

by Mahdi S. Mohammadi, Mehdi Rezaeian
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 90 - Number 7
Year of Publication: 2014
Authors: Mahdi S. Mohammadi, Mehdi Rezaeian
10.5120/15587-4329

Mahdi S. Mohammadi, Mehdi Rezaeian . Towards Affordable Computing: SiftCU a Simple but Elegant GPU-based Implementation of SIFT. International Journal of Computer Applications. 90, 7 ( March 2014), 30-37. DOI=10.5120/15587-4329

@article{ 10.5120/15587-4329,
author = { Mahdi S. Mohammadi, Mehdi Rezaeian },
title = { Towards Affordable Computing: SiftCU a Simple but Elegant GPU-based Implementation of SIFT },
journal = { International Journal of Computer Applications },
issue_date = { March 2014 },
volume = { 90 },
number = { 7 },
month = { March },
year = { 2014 },
issn = { 0975-8887 },
pages = { 30-37 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume90/number7/15587-4329/ },
doi = { 10.5120/15587-4329 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:10:27.037114+05:30
%A Mahdi S. Mohammadi
%A Mehdi Rezaeian
%T Towards Affordable Computing: SiftCU a Simple but Elegant GPU-based Implementation of SIFT
%J International Journal of Computer Applications
%@ 0975-8887
%V 90
%N 7
%P 30-37
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This article presents a fully functional GPU-based implementation of Scale Invariant Feature Transform (SIFT) algorithm. SIFT is a popular image feature extraction algorithm. Although it is a powerful algorithm for image matching but it is also computationally very expensive. This makes it difficult to use especially in real time applications. We purpose to expedite SIFT through GPU-based implementation. There has been some related works on this issue since SIFT was introduced. Our focus is solely on describing GPU-based implementation. We will discuss our implementation in detail. Our implementation is simpler and more efficient than previous works. Part of this paper's purpose is to discuss challenges and strategies related to implementing SIFT like image processing algorithms on GPU. In addition, we are going to present a full comparison between serial implementations of SIFT and our GPU-based implementation, namely siftCU, both in accuracy and time consumption.

References
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Index Terms

Computer Science
Information Sciences

Keywords

CUDA GPGPU GPU programming Image Retrieval SIFT

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