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Comparison and Analysis of Different Feature Extraction Methods versus Noisy Images

by Aziz Makandar, Kanchan Wangi
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 184 - Number 8
Year of Publication: 2022
Authors: Aziz Makandar, Kanchan Wangi
10.5120/ijca2022922054

Aziz Makandar, Kanchan Wangi . Comparison and Analysis of Different Feature Extraction Methods versus Noisy Images. International Journal of Computer Applications. 184, 8 ( Apr 2022), 45-49. DOI=10.5120/ijca2022922054

@article{ 10.5120/ijca2022922054,
author = { Aziz Makandar, Kanchan Wangi },
title = { Comparison and Analysis of Different Feature Extraction Methods versus Noisy Images },
journal = { International Journal of Computer Applications },
issue_date = { Apr 2022 },
volume = { 184 },
number = { 8 },
month = { Apr },
year = { 2022 },
issn = { 0975-8887 },
pages = { 45-49 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume184/number8/32351-2022922054/ },
doi = { 10.5120/ijca2022922054 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:20:58.515607+05:30
%A Aziz Makandar
%A Kanchan Wangi
%T Comparison and Analysis of Different Feature Extraction Methods versus Noisy Images
%J International Journal of Computer Applications
%@ 0975-8887
%V 184
%N 8
%P 45-49
%D 2022
%I Foundation of Computer Science (FCS), NY, USA
Abstract

There are three most effective feature extraction for images they are Speeded Up Robust Feature (SURF), Scale Invariant Feature Transform (SIFT) and Histogram Oriented Gradient (HOG). This study is tended to compare the feature detection strategies for images which have several noises. The effectiveness of this strategies for area unit dignified by observing variety of exact similarity between real images and noisy images established from algorithm. For this work, noisy images are three type gaussian, speckle, salt and pepper.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Feature extraction SIFT SURF HOG and Image matching

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