Integrating ant colony optimization with level set method for biomedical image boundary detection Zastosowanie optymalizacji kolonią mrówek i metody poziomic w wykrywaniu brzegów obrazów biomedycznych
Przeglad Elektrotechniczny, cilt.89, sa.5, ss.218-221, 2013 (Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 89 Sayı: 5
- Basım Tarihi: 2013
- Dergi Adı: Przeglad Elektrotechniczny
- Derginin Tarandığı İndeksler: Scopus
- Sayfa Sayıları: ss.218-221
- Anahtar Kelimeler: Ant colony optimization, Image boundary detection, Initialization, Level set method
- Gazi Üniversitesi Adresli: Evet
Özet
In this paper, ACO-based level set method is introduced to tackle the biomedical image boundary detection problem. The proposed ACO based level set method boundary detection approach is able to construct a pheromone matrix that represents the boundary information presented at each pixel position of the image, according to the movements of a number of ants which are dispatched to move on the image, then this result is initial contour for zero level set function in boundary of image that is segmented. Furthermore, the movements of these ants steers by the local variation of the image's intensity values that it cause the contour move toward the object and exactly found boundaries. ACO-based method determines the initial contour to reduce the iteration steps. Such improvements simplify level set manipulation and lead to more robust segmentation. Experimental results show that the proposed method is can preserve the detail of the object and can be used to reduce the capacity of more computational tasks in research.