Wavelet Analysis: Comparison of Approximation and Details For Mammogram Classification

Image features extraction is an important step in image processing techniques. The features of digital images can be extracted directly from the spatial data or from a different space. Using a different space by special data transforms such wavelet can be helpful to extract specific characteris...

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Main Authors: Brahim Belhaouari, samir, ibrahima, faye, Mohamed M. , Eltoukhy
Format: Article
Language:English
Published: 2009
Subjects:
Online Access:http://scholars.utp.edu.my/id/eprint/2715/
http://scholars.utp.edu.my/id/eprint/2715/1/Wavelet_Analysis_mtokhy_5-8-2009.pdf
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author Brahim Belhaouari, samir
ibrahima, faye
Mohamed M. , Eltoukhy
author_facet Brahim Belhaouari, samir
ibrahima, faye
Mohamed M. , Eltoukhy
author_sort Brahim Belhaouari, samir
building UTP Institutional Repository
collection Online Access
description Image features extraction is an important step in image processing techniques. The features of digital images can be extracted directly from the spatial data or from a different space. Using a different space by special data transforms such wavelet can be helpful to extract specific characteristics from a data. Wavelets prove an efficient representation of image. It decomposes an image into subbands, approximation, horizontal, vertical and diagonal. This paper presents an attempt to find which subband that could be better to used for mammogram classification to detect and diagnose the breast cancer.
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spelling oai:scholars.utp.edu.my:27152017-01-19T08:25:38Z http://scholars.utp.edu.my/id/eprint/2715/ Wavelet Analysis: Comparison of Approximation and Details For Mammogram Classification Brahim Belhaouari, samir ibrahima, faye Mohamed M. , Eltoukhy TK Electrical engineering. Electronics Nuclear engineering Image features extraction is an important step in image processing techniques. The features of digital images can be extracted directly from the spatial data or from a different space. Using a different space by special data transforms such wavelet can be helpful to extract specific characteristics from a data. Wavelets prove an efficient representation of image. It decomposes an image into subbands, approximation, horizontal, vertical and diagonal. This paper presents an attempt to find which subband that could be better to used for mammogram classification to detect and diagnose the breast cancer. 2009 Article NonPeerReviewed application/pdf en http://scholars.utp.edu.my/id/eprint/2715/1/Wavelet_Analysis_mtokhy_5-8-2009.pdf Brahim Belhaouari, samir and ibrahima, faye and Mohamed M. , Eltoukhy (2009) Wavelet Analysis: Comparison of Approximation and Details For Mammogram Classification. Rovisp 2009.
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Brahim Belhaouari, samir
ibrahima, faye
Mohamed M. , Eltoukhy
Wavelet Analysis: Comparison of Approximation and Details For Mammogram Classification
title Wavelet Analysis: Comparison of Approximation and Details For Mammogram Classification
title_full Wavelet Analysis: Comparison of Approximation and Details For Mammogram Classification
title_fullStr Wavelet Analysis: Comparison of Approximation and Details For Mammogram Classification
title_full_unstemmed Wavelet Analysis: Comparison of Approximation and Details For Mammogram Classification
title_short Wavelet Analysis: Comparison of Approximation and Details For Mammogram Classification
title_sort wavelet analysis: comparison of approximation and details for mammogram classification
topic TK Electrical engineering. Electronics Nuclear engineering
url http://scholars.utp.edu.my/id/eprint/2715/
http://scholars.utp.edu.my/id/eprint/2715/1/Wavelet_Analysis_mtokhy_5-8-2009.pdf