Image Segmentation with an Improved Active Contour
Xiao Jiang · 2004
Image segmentation is a key process from image processing to image analysis, which is also a basic technique in Computer Vision. In this paper the authors first introduce the theory of the active contour. The active contour is something different from the common segmentation method. During the processing, the active contour finds the optimal value for every pixel in a small domain but also considers the relationship between different pixels as well. And as a result, the active contour can give out a smooth and continuous contour of the aim object. The basic idea of the active contour is to make the contour move to the destination with the internal and external energy. When the contour moves to the target point the total energy of the contour becomes minimum. Traditionally the external force of the active contour is given by the gradient potential energy, which has some insurmountable shortcomings, thus it cannot direct the contour to move to the destination correctly. Due to the character of the edge, the diffuse method is applied to the gradient of the edge i.e. the gradient vector flow (GVF). The GVF field maintains the merit of the gradient in the range nearby the edge but also diffuses the energy field to the slowly changed range as well, where the traditional gradient energy is very little. The GVF not only expands the effective range of the energy field but also enhances the ability to deal with the concave surface as well. The experimental results show the effectivity of the method.