Open AccessActive contour model based on fuzzy c‐means for image segmentation
Author(s) -
Jin Ri,
Weng Guirong
Publication year - 2019
Publication title -
electronics letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.375
H-Index - 146
eISSN - 1350-911X
pISSN - 0013-5194
DOI - 10.1049/el.2018.5307
Subject(s) - active contour model , robustness (evolution) , fuzzy logic , artificial intelligence , segmentation , image segmentation , computer vision , computer science , image (mathematics) , pattern recognition (psychology) , contour line , mathematics , geography , cartography , biochemistry , chemistry , gene
In this Letter, the authors propose an active contour model based on the fuzzy c‐means method. Using fuzzy c‐means to calculate the values of two types of cluster centres for all points in the image domain, by which local fitting functions in traditional models are substituted. Since the values are calculated before curve evolution, the proposed model can segment images with intensity inhomogeneity efficiently. Furthermore, it has the good robustness to initial contour. The effectiveness of the proposed model is tested by experiments on some synthetic and real images.