Unsupervised segmentation of gray level Markov model textures with hierarchical self organizing maps

Goktepe M., Yalabik N., Atalay V.

13th International Conference on Pattern Recognition, ICPR 1996, Vienna, Avusturya, 25 - 29 Ağustos 1996, cilt.4, ss.90-94 identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Cilt numarası: 4
  • Doi Numarası: 10.1109/icpr.1996.547240
  • Basıldığı Şehir: Vienna
  • Basıldığı Ülke: Avusturya
  • Sayfa Sayıları: ss.90-94
  • Orta Doğu Teknik Üniversitesi Adresli: Evet

Özet

Segmentation of gray level images into regions of uniform texture is investigated. An unsupervised approach through the use of Kohonen's self organizing map (SOM) and a multilayer version of it, the hierarchical self organizing map (HSOM), is employed to find the regions in an image composed of textures from different classes. For testing, gray level artificial textured images modeled as Markov random fields are used as the input. No parameter estimation is done. The size and the topology of SOM and HSOM are independent from the size of the input image. The segmentation results are very promising. © 1996 IEEE.