Mammogram Images Classification using Gray Level Co-occurence Matrices

Severoglu N.

24th Signal Processing and Communication Application Conference (SIU), Zonguldak, Turkey, 16 - 19 May 2016, pp.1781-1784, (Full Text) identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Volume:
  • Doi Number: 10.1109/siu.2016.7496106
  • City: Zonguldak
  • Country: Turkey
  • Page Numbers: pp.1781-1784
  • Gazi University Affiliated: Yes

Abstract

The aim of study was to classify mammogram images using Gray Level Co-occurence Matrices - GLCM. In study, morphological image processing was used as a preprocessing method to detect breast regions. Both GLCM texture features; contrast, correlation, energy and homogeneity and statistical features; mean, variance, skewness and kurtosis are extracted from the breast regions on images. The images are classified by using (Support Vector Machines - SVM) and (Nearest Neighbor - NN) methods. GLCM and statistical features are examined on classification accuracy.