영상분할을 위한 이완법의 초기확률 = Initial Probability of Relaxation Process for Image Segmentation

다국어 초록 (Multilingual Abstract)

Two approaches to the initial probability for the image segmentation using the relaxation process are studied. The first initial probabilities are defined based on the image histogram. In this case, the convergence rate of label probability is fast and an image is segmented to the roughly segmented regions. Therefore this method is suitable for the large size general image. Another initial probability is derived from the local feature of an image. Although the convergence rate of pixel labeling is relatively slow, an image is segmented to feature regions with low segmentation error. Experimental results show that it is very useful for the medical image segamentation with the low contrast and small size area of interest.