Quantitative and qualitative analyses of Dimension Reduction Methods effect on the classification of mammographic images
This paper presents a comparative study of dimension reduction methods combined with wavelet transform. This study is carried out for mammographic image classification. It is performed in three stages: extraction of features characterizing the tissue areas then a dimension reduction was achieved by four different methods of discrimination and finally the classification phase was carried. We have experimented for this purpose K-Nearest neighbours classifier.
Results show the classification accuracy in some cases has reached 100%. We also found that generally the classification accuracy increases with the dimension but stabilizes after a certain value which is approximately d=60. We also present the results as a projection of onto a two-dimensional space. In some cases we observed a clear separation between normal images and abnormal ones.
Keywords: Dimension reduction, Classification, Feature extraction, Mammographic images.
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ABOUT THE AUTHORS
Nezha Hamdi
Cadi Ayyad University
Sar Haddo Bouazza
Cadi Ayyad University
Khalid Auhmani
Cadi Ayyad University
Moha M\'rabet Hassani
Cadi Ayyad University
Nezha Hamdi
Cadi Ayyad University
Sar Haddo Bouazza
Cadi Ayyad University
Khalid Auhmani
Cadi Ayyad University
Moha M\'rabet Hassani
Cadi Ayyad University