Active contour with selective local or global segmentation for intensity inhomogeneous image

In this paper, a novel algorithm for intensity inhomogeneous image segmentation is proposed. The presented method introduces a signed pressure force function using the local information of the image to be segmented. Thus, this model can work with heterogeneous images. In addition, by taking the advantages of Geodesic active contour (GAC) and Chan-Vese (C-V) model, the method could deal with objects even with discrete /blur boundaries and gives exact results in detecting object boundaries. Experimental results demonstrate that the proposed model is effective in segmenting inhomogeneous images and promising in pattern recognition.