Open AccessRobust active contours for fast image segmentation
Author(s) -
Ding Keyan,
Weng Guirong
Publication year - 2016
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.2016.2654
Subject(s) - active contour model , image segmentation , artificial intelligence , segmentation , computer vision , scale space segmentation , computer science , image (mathematics) , intensity (physics) , segmentation based object categorization , energy (signal processing) , pattern recognition (psychology) , mathematics , physics , optics , statistics
A robust active contour model is proposed for fast image segmentation. By introducing the intensity fitting energy in a local region, the proposed model can segment the images with intensity inhomogeneity efficiently. Since the local fitting functions are computed before curve evolution, the proposed model is insensitive to initialisation and has a high segmentation efficiency. Experiments on several synthetic and real images have proved the effectiveness of the proposed model.