Open AccessA Comparative Study of Dimension Reduction Methods Combined with Wavelet Transform Applied to the Classification of Mammographic Images
Author(s) -
Nezha Hamdi,
Khalid Auhmani,
Moha M’Rabet Hassani
Publication year - 2014
Publication title -
international journal of computer science and information technology/international journal of computer science and information technology (chennai. print)
Language(s) - English
Resource type - Journals
eISSN - 0975-4660
pISSN - 0975-3826
DOI - 10.5121/ijcsit.2014.6611
Subject(s) - computer science , wavelet , artificial intelligence , dimension (graph theory) , dimensionality reduction , wavelet transform , pattern recognition (psychology) , reduction (mathematics) , computer vision , mathematics , geometry , pure mathematics
In this paper, we present a comparative study of dimension reduction methods combined with wavelet\udtransform. This study is carried out for mammographic image classification. It is performed in three stages:\udextraction of features characterizing the tissue areas then a dimension reduction was achieved by four\uddifferent methods of discrimination and finally the classification phase was carried. We have late compared\udthe performance of two classifiers KNN and decision tree.\udResults show the classification accuracy in some cases has reached 100%. We also found that generally the\udclassification accuracy increases with the dimension but stabilizes after a certain value which is\udapproximately d=60.\u