Mammogram Images Classification using Gray Level Co-occurence Matrices

Severoglu N.

24th Signal Processing and Communication Application Conference (SIU), Zonguldak, Türkiye, 16 - 19 Mayıs 2016, ss.1781-1784 identifier identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Cilt numarası:
  • Doi Numarası: 10.1109/siu.2016.7496106
  • Basıldığı Şehir: Zonguldak
  • Basıldığı Ülke: Türkiye
  • Sayfa Sayıları: ss.1781-1784
  • Gazi Üniversitesi Adresli: Evet

Özet

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.