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Advance Technique for Feature Extraction and Image Compression

by Arvind Kourav, Prashant Singh
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 68 - Number 21
Year of Publication: 2013
Authors: Arvind Kourav, Prashant Singh
10.5120/11703-7289

Arvind Kourav, Prashant Singh . Advance Technique for Feature Extraction and Image Compression. International Journal of Computer Applications. 68, 21 ( April 2013), 22-27. DOI=10.5120/11703-7289

@article{ 10.5120/11703-7289,
author = { Arvind Kourav, Prashant Singh },
title = { Advance Technique for Feature Extraction and Image Compression },
journal = { International Journal of Computer Applications },
issue_date = { April 2013 },
volume = { 68 },
number = { 21 },
month = { April },
year = { 2013 },
issn = { 0975-8887 },
pages = { 22-27 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume68/number21/11703-7289/ },
doi = { 10.5120/11703-7289 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:28:31.182590+05:30
%A Arvind Kourav
%A Prashant Singh
%T Advance Technique for Feature Extraction and Image Compression
%J International Journal of Computer Applications
%@ 0975-8887
%V 68
%N 21
%P 22-27
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

For image processing, it is very necessary that the selection of transform. In this paper, a comparative analysis of curve let transform with other transform for image processing . In this we proposed the applications of curve let transform in the field of image Compression ,phase recognition and feature extraction. For higher compression with quality reconstruction . The Wavelets gave a different aspect to the compression. Curvelet Transform gives better results in terms of PSNR. Face recognition is very important for many applications such as: video surveillance, criminal investigations and forensic applications, secure electronic banking, mobile phones, credit cards, secure access to buildings . The curve let transform is a multi scale directional transform, which allows an almost optimal non adaptive sparse representation of objects with edges. Curve let have also proven useful in diverse fields beyond the traditional image processing application, Curvelet transform improve recognition accuracy with featature extraction extraction algorithms PCA, LDA,ICA and NMF.

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Index Terms

Computer Science
Information Sciences

Keywords

Image processing Image Compression Feature Extraction Curvelet transform Wavelet Transform

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