Fast localised active contour for inhomogeneous image segmentation

Abstract

The localised active contour framework has been widely used for image segmentation because it provides reliable results for inhomogeneous images. However, its computational complexity remains an issue. In this study, the authors introduce a fast algorithm based on the localised active contour framework. A key concept of the proposed algorithm is its consideration of the curve evolution based on the speed function only at active points that change across time, rather than at all points in a narrow band. This approach reduces computational time in the localised active contour. The authors additionally propose a modified speed function to address inhomogeneous image segmentation. The experimental results demonstrate significant advantages of the proposed method over existing methods, both in terms of computational efficiency and segmentation accuracy, for homogeneous and inhomogeneous images.