Active contours driven by novel LGIF energies for image segmentation
Bin Han, Yiquan Wu · Electronics Letters · 2017
An active contour model driven by novel local and global intensity fitting (LGIF) energies for image segmentation is presented. First, the GIF energy is defined by the squared‐chord distance, which is more robust to noise. Second, the LIF energy is defined by the Lorentzian distance to calculate the local intensity information, which improves the generality of the presented model. Experiments are carried out on synthetic and real images and the results illustrate that the presented model can obtain higher segmentation accuracy and better segmentation efficiency; moreover, it is not sensitive to initial contour.