Image segmentation by relaxation using constraint satisfaction neural network

Kurugollu F., Sankur B., Harmanci A.

IMAGE AND VISION COMPUTING, cilt.20, sa.7, ss.483-497, 2002 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 20 Sayı: 7
  • Basım Tarihi: 2002
  • Doi Numarası: 10.1016/s0262-8856(02)00023-9
  • Dergi Adı: IMAGE AND VISION COMPUTING
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.483-497
  • İstanbul Teknik Üniversitesi Adresli: Hayır

Özet

The problem of image segmentation using constraint satisfaction neural networks (CSNN) has been considered. Several variations of the CSNN theme have been advanced to improve its performance or to explore new structures. These new segmentation algorithms are based on interplay of additional constraints, of varying the organization of the network or modifying the relaxation scheme. The proposed schemes are tested comparatively on a bank of test images as well as real world images. (C) 2002 Elsevier Science B.V. All rights reserved.