Digital Mammograms Classification Using a Wavelet Based Feature Extraction Method

This paper introduces a new method of feature extraction from Wavelet coefficients for classification of digital mammograms. A matrix is constructed by putting Wavelet coefficients of each image of a building set as a row vector. The method consists then on selecting by threshold, the columns which...

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Main Authors: Brahim Belhaouari, samir, Ibrahima, Faye
Format: Conference or Workshop Item
Language:English
Subjects:
Online Access:http://scholars.utp.edu.my/id/eprint/937/
http://scholars.utp.edu.my/id/eprint/937/1/New_Feature_Extaction_Method.pdf
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author Brahim Belhaouari, samir
Ibrahima, Faye
author_facet Brahim Belhaouari, samir
Ibrahima, Faye
author_sort Brahim Belhaouari, samir
building UTP Institutional Repository
collection Online Access
description This paper introduces a new method of feature extraction from Wavelet coefficients for classification of digital mammograms. A matrix is constructed by putting Wavelet coefficients of each image of a building set as a row vector. The method consists then on selecting by threshold, the columns which will maximize the Euclidian distances between the different class representatives. The selected columns are then used as features for classification. The method is tested using a set of images provided by the Mammographic Image Analysis Society (MIAS) to classify between normal and abnormal and then between benign and malignant tissues. For both classifications, a high accuracy rate (98%) is achieved.
first_indexed 2025-11-13T07:24:25Z
format Conference or Workshop Item
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institution Universiti Teknologi Petronas
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language English
last_indexed 2025-11-13T07:24:25Z
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spelling oai:scholars.utp.edu.my:9372017-01-19T08:27:45Z http://scholars.utp.edu.my/id/eprint/937/ Digital Mammograms Classification Using a Wavelet Based Feature Extraction Method Brahim Belhaouari, samir Ibrahima, Faye TK Electrical engineering. Electronics Nuclear engineering This paper introduces a new method of feature extraction from Wavelet coefficients for classification of digital mammograms. A matrix is constructed by putting Wavelet coefficients of each image of a building set as a row vector. The method consists then on selecting by threshold, the columns which will maximize the Euclidian distances between the different class representatives. The selected columns are then used as features for classification. The method is tested using a set of images provided by the Mammographic Image Analysis Society (MIAS) to classify between normal and abnormal and then between benign and malignant tissues. For both classifications, a high accuracy rate (98%) is achieved. Conference or Workshop Item PeerReviewed application/pdf en http://scholars.utp.edu.my/id/eprint/937/1/New_Feature_Extaction_Method.pdf Brahim Belhaouari, samir and Ibrahima, Faye Digital Mammograms Classification Using a Wavelet Based Feature Extraction Method. In: the International Conference on Intelligent & Advanced Systems 2010.
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Brahim Belhaouari, samir
Ibrahima, Faye
Digital Mammograms Classification Using a Wavelet Based Feature Extraction Method
title Digital Mammograms Classification Using a Wavelet Based Feature Extraction Method
title_full Digital Mammograms Classification Using a Wavelet Based Feature Extraction Method
title_fullStr Digital Mammograms Classification Using a Wavelet Based Feature Extraction Method
title_full_unstemmed Digital Mammograms Classification Using a Wavelet Based Feature Extraction Method
title_short Digital Mammograms Classification Using a Wavelet Based Feature Extraction Method
title_sort digital mammograms classification using a wavelet based feature extraction method
topic TK Electrical engineering. Electronics Nuclear engineering
url http://scholars.utp.edu.my/id/eprint/937/
http://scholars.utp.edu.my/id/eprint/937/1/New_Feature_Extaction_Method.pdf