A Survey on Image Segmentation Using Geometric Active Contour Model

Abstract

Image segmentation is a classical and crucial problem in the fields of computer vision and image understanding. Since Kass et al. proposed the seminal model, i.e. snake, active contour model has rapid development and becomes a research hotspot. It mainly includes parametric active contour model and geometric active contour model. Geometric active contour model has many advantages over parametric active contour model, such as computational simplicity and the ability to change curve topology during deformation. Therefore, this paper gives a review on geometric active contour model, the three types of active contour models, i.e. edge-based, region-based and edge-region based models are presented, their advantages and drawbacks are summarized, a number of improvements are analyzed in detail. Finally, the paper makes prospect for the future of active contour model.