Variational methods for image segmentation by using the level set function and its applications
김선희 · Seoul National University Open Repository (Seoul National University) · 2012
This dissertation concerns the variational methods for image segmentation by using the level set function. We classify images into two categories: two-phase images and multi-phase images. The multi-phase segmentation problem is unstable in the sense that the segmentation result depends significantly on the number of different phases given a priori. This is a critical issue in the multi-phase segmentation and we want to automatically obtain the phase number through the process. First, we survey the previous two and multi-phase segmentation models and then propose a new segmentation method for multi-phase images, which can determine the phase number in the process. Finally, we show some applications of a level set based segmentation method in realistic problems: the automatic number plate recognition and the medical field.