Edge detection using clustering algorithms


Sirin T., Saglam M. I., Erer I., Gokmen M.

WSEAS Transactions on Computers, cilt.4, sa.5, ss.417-423, 2005 (Scopus) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 4 Sayı: 5
  • Basım Tarihi: 2005
  • Dergi Adı: WSEAS Transactions on Computers
  • Derginin Tarandığı İndeksler: Scopus
  • Sayfa Sayıları: ss.417-423
  • Anahtar Kelimeler: Canny, Clustering, Edge detection, GED, K-Means, SOM
  • İstanbul Teknik Üniversitesi Adresli: Evet

Özet

Edge detection is an important topic in image processing and a main tool in pattern recognition and image segmentation. Many edge detection techniques are available in the literature. 'A number of recent edge detectors are multiscale and include three main processing steps: smoothing, differentiation and labeling' (Ziau and Tabbone, 1997). This paper, presents a proposed method which is suitable for edge detection in images. This method is based on the use of the clustering algorithms (Self-Organizing Map (SOM), K-Means) and a gray scale edge detector (Canny, Generalized Edge Detector (GED)). It is shown that using the grayscale edge detectors may miss some parts of the edges which can be found using the proposed method.