AIRCC's International Journal of Computer Science and Information Technology

The PDF file you selected should load here if your Web browser has a PDF reader plug-in installed (for example, a recent version of Adobe Acrobat Reader).

If you would like more information about how to print, save, and work with PDFs, Highwire Press provides a helpful Frequently Asked Questions about PDFs.

Alternatively, you can download the PDF file directly to your computer, from where it can be opened using a PDF reader. To download the PDF, click the Download link above.

Fullscreen Fullscreen Off


In this paper, we present 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 late compared the performance of two classifiers KNN and decision tree.

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.


Keywords

Dimension Reduction, Classification, Feature Extraction, Mammographic Images.
User
Notifications
Font Size